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\n  \n 2022\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n CUF-Links: Continuous and Ubiquitous FAIRness Linkages for Reproducible Research.\n \n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n Computer, 55(8): 20–30. August 2022.\n \n\n\n\n
\n\n\n\n \n \n \"CUF-Links:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{foster_cuf-links_2022,\n\ttitle = {{CUF}-{Links}: {Continuous} and {Ubiquitous} {FAIRness} {Linkages} for {Reproducible} {Research}},\n\tvolume = {55},\n\tissn = {0018-9162, 1558-0814},\n\tshorttitle = {{CUF}-{Links}},\n\turl = {https://ieeexplore.ieee.org/document/9847317/},\n\tdoi = {10.1109/MC.2022.3160876},\n\tnumber = {8},\n\turldate = {2022-08-08},\n\tjournal = {Computer},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tmonth = aug,\n\tyear = {2022},\n\tpages = {20--30},\n}\n\n
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\n \n\n \n \n \n \n \n \n Sharing Begins at Home: How Continuous and Ubiquitous FAIRness Can Enhance Research Productivity and Data Reuse.\n \n \n \n \n\n\n \n Dempsey, W. P; Foster, I.; Fraser, S.; and Kesselman, C.\n\n\n \n\n\n\n Harvard Data Science Review. July 2022.\n \n\n\n\n
\n\n\n\n \n \n \"SharingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{dempsey_sharing_2022,\n\ttitle = {Sharing {Begins} at {Home}: {How} {Continuous} and {Ubiquitous} {FAIRness} {Can} {Enhance} {Research} {Productivity} and {Data} {Reuse}},\n\tshorttitle = {Sharing {Begins} at {Home}},\n\turl = {https://hdsr.mitpress.mit.edu/pub/qjpg8oik},\n\tdoi = {10.1162/99608f92.44d21b86},\n\tlanguage = {en},\n\turldate = {2022-08-04},\n\tjournal = {Harvard Data Science Review},\n\tauthor = {Dempsey, William P and Foster, Ian and Fraser, Scott and Kesselman, Carl},\n\tmonth = jul,\n\tyear = {2022},\n}\n\n
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\n \n\n \n \n \n \n \n \n FaceBase: A Community-Driven Hub for Data-Intensive Research.\n \n \n \n \n\n\n \n Schuler, R.; Bugacov, A.; Hacia, J.; Ho, T.; Iwata, J.; Pearlman, L.; Samuels, B.; Williams, C.; Zhao, Z.; Kesselman, C.; and Chai, Y.\n\n\n \n\n\n\n Journal of Dental Research,002203452211079. July 2022.\n \n\n\n\n
\n\n\n\n \n \n \"FaceBase:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{schuler_facebase_2022,\n\ttitle = {{FaceBase}: {A} {Community}-{Driven} {Hub} for {Data}-{Intensive} {Research}},\n\tissn = {0022-0345, 1544-0591},\n\tshorttitle = {{FaceBase}},\n\turl = {http://journals.sagepub.com/doi/10.1177/00220345221107905},\n\tdoi = {10.1177/00220345221107905},\n\tabstract = {The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers “self-curate” their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase’s operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.},\n\tlanguage = {en},\n\turldate = {2022-08-04},\n\tjournal = {Journal of Dental Research},\n\tauthor = {Schuler, R.E. and Bugacov, A. and Hacia, J.G. and Ho, T.V. and Iwata, J. and Pearlman, L. and Samuels, B.D. and Williams, C. and Zhao, Z. and Kesselman, C. and Chai, Y.},\n\tmonth = jul,\n\tyear = {2022},\n\tpages = {002203452211079},\n}\n\n
\n
\n\n\n
\n The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers “self-curate” their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase’s operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.\n
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\n \n\n \n \n \n \n \n \n Regional synapse gain and loss accompany memory formation in larval zebrafish.\n \n \n \n \n\n\n \n Dempsey, W. P.; Du, Z.; Nadtochiy, A.; Smith, C. D.; Czajkowski, K.; Andreev, A.; Robson, D. N.; Li, J. M.; Applebaum, S.; Truong, T. V.; Kesselman, C.; Fraser, S. E.; and Arnold, D. B.\n\n\n \n\n\n\n Proceedings of the National Academy of Sciences, 119(3): e2107661119. January 2022.\n \n\n\n\n
\n\n\n\n \n \n \"RegionalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{dempsey_regional_2022,\n\ttitle = {Regional synapse gain and loss accompany memory formation in larval zebrafish},\n\tvolume = {119},\n\tissn = {0027-8424, 1091-6490},\n\turl = {http://www.pnas.org/lookup/doi/10.1073/pnas.2107661119},\n\tdoi = {10.1073/pnas.2107661119},\n\tabstract = {Defining the structural and functional changes in the nervous system underlying learning and memory represents a major challenge for modern neuroscience. Although changes in neuronal activity following memory formation have been studied [B. F. Grewe et al.,\n              Nature\n              543, 670–675 (2017); M. T. Rogan, U. V. Stäubli, J. E. LeDoux,\n              Nature\n              390, 604–607 (1997)], the underlying structural changes at the synapse level remain poorly understood. Here, we capture synaptic changes in the midlarval zebrafish brain that occur during associative memory formation by imaging excitatory synapses labeled with recombinant probes using selective plane illumination microscopy. Imaging the same subjects before and after classical conditioning at single-synapse resolution provides an unbiased mapping of synaptic changes accompanying memory formation. In control animals and animals that failed to learn the task, there were no significant changes in the spatial patterns of synapses in the pallium, which contains the equivalent of the mammalian amygdala and is essential for associative learning in teleost fish [M. Portavella, J. P. Vargas, B. Torres, C. Salas,\n              Brain Res. Bull\n              . 57, 397–399 (2002)]. In zebrafish that formed memories, we saw a dramatic increase in the number of synapses in the ventrolateral pallium, which contains neurons active during memory formation and retrieval. Concurrently, synapse loss predominated in the dorsomedial pallium. Surprisingly, we did not observe significant changes in the intensity of synaptic labeling, a proxy for synaptic strength, with memory formation in any region of the pallium. Our results suggest that memory formation due to classical conditioning is associated with reciprocal changes in synapse numbers in the pallium.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-01-14},\n\tjournal = {Proceedings of the National Academy of Sciences},\n\tauthor = {Dempsey, William P. and Du, Zhuowei and Nadtochiy, Anna and Smith, Colton D. and Czajkowski, Karl and Andreev, Andrey and Robson, Drew N. and Li, Jennifer M. and Applebaum, Serina and Truong, Thai V. and Kesselman, Carl and Fraser, Scott E. and Arnold, Don B.},\n\tmonth = jan,\n\tyear = {2022},\n\tpages = {e2107661119},\n}\n\n
\n
\n\n\n
\n Defining the structural and functional changes in the nervous system underlying learning and memory represents a major challenge for modern neuroscience. Although changes in neuronal activity following memory formation have been studied [B. F. Grewe et al., Nature 543, 670–675 (2017); M. T. Rogan, U. V. Stäubli, J. E. LeDoux, Nature 390, 604–607 (1997)], the underlying structural changes at the synapse level remain poorly understood. Here, we capture synaptic changes in the midlarval zebrafish brain that occur during associative memory formation by imaging excitatory synapses labeled with recombinant probes using selective plane illumination microscopy. Imaging the same subjects before and after classical conditioning at single-synapse resolution provides an unbiased mapping of synaptic changes accompanying memory formation. In control animals and animals that failed to learn the task, there were no significant changes in the spatial patterns of synapses in the pallium, which contains the equivalent of the mammalian amygdala and is essential for associative learning in teleost fish [M. Portavella, J. P. Vargas, B. Torres, C. Salas, Brain Res. Bull . 57, 397–399 (2002)]. In zebrafish that formed memories, we saw a dramatic increase in the number of synapses in the ventrolateral pallium, which contains neurons active during memory formation and retrieval. Concurrently, synapse loss predominated in the dorsomedial pallium. Surprisingly, we did not observe significant changes in the intensity of synaptic labeling, a proxy for synaptic strength, with memory formation in any region of the pallium. Our results suggest that memory formation due to classical conditioning is associated with reciprocal changes in synapse numbers in the pallium.\n
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\n  \n 2021\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n Model-Adaptive Interface Generation for Data-Driven Discovery.\n \n \n \n \n\n\n \n Tangmunarunkit, H.; Shafaeibejestan, A.; Chudy, J.; Czajkowski, K.; Schuler, R.; and Kesselman, C.\n\n\n \n\n\n\n arXiv:2110.01781 [cs]. October 2021.\n arXiv: 2110.01781\n\n\n\n
\n\n\n\n \n \n \"Model-AdaptivePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{tangmunarunkit_model-adaptive_2021,\n\ttitle = {Model-{Adaptive} {Interface} {Generation} for {Data}-{Driven} {Discovery}},\n\turl = {http://arxiv.org/abs/2110.01781},\n\tabstract = {Discovery of new knowledge is increasingly data-driven, predicated on a team's ability to collaboratively create, find, analyze, retrieve, and share pertinent datasets over the duration of an investigation. This is especially true in the domain of scientific discovery where generation, analysis, and interpretation of data are the fundamental mechanisms by which research teams collaborate to achieve their shared scientific goal. Data-driven discovery in general, and scientific discovery in particular, is distinguished by complex and diverse data models and formats that evolve over the lifetime of an investigation. While databases and related information systems have the potential to be valuable tools in the discovery process, developing effective interfaces for data-driven discovery remains a roadblock to the application of database technology as an essential tool in scientific investigations. In this paper, we present a model-adaptive approach to creating interaction environments for data-driven discovery of scientific data that automatically generates interactive user interfaces for editing, searching, and viewing scientific data based entirely on introspection of an extended relational data model. We have applied model-adaptive interface generation to many active scientific investigations spanning domains of proteomics, bioinformatics, neuroscience, occupational therapy, stem cells, genitourinary, craniofacial development, and others. We present the approach, its implementation, and its evaluation through analysis of its usage in diverse scientific settings.},\n\turldate = {2022-01-15},\n\tjournal = {arXiv:2110.01781 [cs]},\n\tauthor = {Tangmunarunkit, Hongsuda and Shafaeibejestan, Aref and Chudy, Joshua and Czajkowski, Karl and Schuler, Robert and Kesselman, Carl},\n\tmonth = oct,\n\tyear = {2021},\n\tnote = {arXiv: 2110.01781},\n\tkeywords = {Computer Science - Human-Computer Interaction},\n}\n\n
\n
\n\n\n
\n Discovery of new knowledge is increasingly data-driven, predicated on a team's ability to collaboratively create, find, analyze, retrieve, and share pertinent datasets over the duration of an investigation. This is especially true in the domain of scientific discovery where generation, analysis, and interpretation of data are the fundamental mechanisms by which research teams collaborate to achieve their shared scientific goal. Data-driven discovery in general, and scientific discovery in particular, is distinguished by complex and diverse data models and formats that evolve over the lifetime of an investigation. While databases and related information systems have the potential to be valuable tools in the discovery process, developing effective interfaces for data-driven discovery remains a roadblock to the application of database technology as an essential tool in scientific investigations. In this paper, we present a model-adaptive approach to creating interaction environments for data-driven discovery of scientific data that automatically generates interactive user interfaces for editing, searching, and viewing scientific data based entirely on introspection of an extended relational data model. We have applied model-adaptive interface generation to many active scientific investigations spanning domains of proteomics, bioinformatics, neuroscience, occupational therapy, stem cells, genitourinary, craniofacial development, and others. We present the approach, its implementation, and its evaluation through analysis of its usage in diverse scientific settings.\n
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\n \n\n \n \n \n \n \n \n Translating the grid: How a translational approach shaped the development of grid computing.\n \n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n Journal of Computational Science, 52: 101214. May 2021.\n \n\n\n\n
\n\n\n\n \n \n \"TranslatingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{foster_translating_2021,\n\ttitle = {Translating the grid: {How} a translational approach shaped the development of grid computing},\n\tvolume = {52},\n\tissn = {18777503},\n\tshorttitle = {Translating the grid},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S187775032030510X},\n\tdoi = {10.1016/j.jocs.2020.101214},\n\tlanguage = {en},\n\turldate = {2022-01-14},\n\tjournal = {Journal of Computational Science},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tmonth = may,\n\tyear = {2021},\n\tpages = {101214},\n}\n\n
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\n \n\n \n \n \n \n \n \n Bayesian metamodeling of complex biological systems across varying representations.\n \n \n \n \n\n\n \n Raveh, B.; Sun, L.; White, K. L.; Sanyal, T.; Tempkin, J.; Zheng, D.; Bharath, K.; Singla, J.; Wang, C.; Zhao, J.; Li, A.; Graham, N. A.; Kesselman, C.; Stevens, R. C.; and Sali, A.\n\n\n \n\n\n\n Proceedings of the National Academy of Sciences, 118(35): e2104559118. August 2021.\n \n\n\n\n
\n\n\n\n \n \n \"BayesianPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{raveh_bayesian_2021,\n\ttitle = {Bayesian metamodeling of complex biological systems across varying representations},\n\tvolume = {118},\n\tissn = {0027-8424, 1091-6490},\n\turl = {http://www.pnas.org/lookup/doi/10.1073/pnas.2104559118},\n\tdoi = {10.1073/pnas.2104559118},\n\tabstract = {Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic β-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic β-Cell Consortium.},\n\tlanguage = {en},\n\tnumber = {35},\n\turldate = {2022-01-14},\n\tjournal = {Proceedings of the National Academy of Sciences},\n\tauthor = {Raveh, Barak and Sun, Liping and White, Kate L. and Sanyal, Tanmoy and Tempkin, Jeremy and Zheng, Dongqing and Bharath, Kala and Singla, Jitin and Wang, Chenxi and Zhao, Jihui and Li, Angdi and Graham, Nicholas A. and Kesselman, Carl and Stevens, Raymond C. and Sali, Andrej},\n\tmonth = aug,\n\tyear = {2021},\n\tpages = {e2104559118},\n}\n\n
\n
\n\n\n
\n Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic β-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic β-Cell Consortium.\n
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\n \n\n \n \n \n \n \n \n Making Common Fund data more findable: Catalyzing a Data Ecosystem.\n \n \n \n \n\n\n \n Charbonneau, A. L; Brady, A.; Canchi, S.; Carter, R.; Chard, K.; Clarke, D. J.; Creasy, H. H; D’Arcy, M.; Giglio, M.; Gingrich, A.; Harris, R. M; Hodges, T. K; Jeon, M.; Kropiwnicki, E.; Lim, M. C.; Liming, R. L.; Mandal, M.; Munro, J. B; Nadendla, S.; Romano, C.; Rocca-Serra, P.; Schuler, R. E.; Waldrop, A.; Williams, C.; Word, K.; Sansone, S.; Ma’ayan, A.; Wagner, R.; Foster, I.; Kesselman, C.; Brown, C. T.; and White, O.\n\n\n \n\n\n\n Technical Report Bioinformatics, November 2021.\n \n\n\n\n
\n\n\n\n \n \n \"MakingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@techreport{charbonneau_making_2021,\n\ttype = {preprint},\n\ttitle = {Making {Common} {Fund} data more findable: {Catalyzing} a {Data} {Ecosystem}},\n\tshorttitle = {Making {Common} {Fund} data more findable},\n\turl = {http://biorxiv.org/lookup/doi/10.1101/2021.11.05.467504},\n\tabstract = {Abstract\n          The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables users to discover datasets from across the Common Fund without requiring the data owners to move, reformat, or rehost those data. The CFDEs federation system is centered on a catalog that ingests metadata from individual Common Fund Program’s Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2), supports the wide variety of data types and metadata terms used by the individual DCCs and is designed to enable easy expansion to accommodate new data types.},\n\tlanguage = {en},\n\turldate = {2022-01-14},\n\tinstitution = {Bioinformatics},\n\tauthor = {Charbonneau, Amanda L and Brady, Arthur and Canchi, Saranya and Carter, Robert and Chard, Kyle and Clarke, Daniel J.B. and Creasy, Heather H and D’Arcy, Mike and Giglio, Michelle and Gingrich, Alicia and Harris, Rayna M and Hodges, Theresa K and Jeon, Minji and Kropiwnicki, Eryk and Lim, Marisa C.W. and Liming, R. Lee and Mandal, Meisha and Munro, James B and Nadendla, Suvarna and Romano, Cia and Rocca-Serra, Philippe and Schuler, Robert E. and Waldrop, Alex and Williams, Cris and Word, Karen and Sansone, Susanna-Assunta and Ma’ayan, Avi and Wagner, Rick and Foster, Ian and Kesselman, Carl and Brown, C. Titus and White, Owen},\n\tmonth = nov,\n\tyear = {2021},\n\tdoi = {10.1101/2021.11.05.467504},\n}\n\n
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\n Abstract The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables users to discover datasets from across the Common Fund without requiring the data owners to move, reformat, or rehost those data. The CFDEs federation system is centered on a catalog that ingests metadata from individual Common Fund Program’s Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2), supports the wide variety of data types and metadata terms used by the individual DCCs and is designed to enable easy expansion to accommodate new data types.\n
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\n \n\n \n \n \n \n \n \n CHiSEL: a user-oriented framework for simplifing database evolution.\n \n \n \n \n\n\n \n Schuler, R.; and Kesselman, C.\n\n\n \n\n\n\n Distributed and Parallel Databases, 39(2): 483–543. June 2021.\n \n\n\n\n
\n\n\n\n \n \n \"CHiSEL:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{schuler_chisel_2021,\n\ttitle = {{CHiSEL}: a user-oriented framework for simplifing database evolution},\n\tvolume = {39},\n\tissn = {0926-8782, 1573-7578},\n\tshorttitle = {{CHiSEL}},\n\turl = {https://link.springer.com/10.1007/s10619-020-07314-x},\n\tdoi = {10.1007/s10619-020-07314-x},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-01-14},\n\tjournal = {Distributed and Parallel Databases},\n\tauthor = {Schuler, Robert and Kesselman, Carl},\n\tmonth = jun,\n\tyear = {2021},\n\tpages = {483--543},\n}\n\n
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\n \n\n \n \n \n \n \n \n New system for archiving integrative structures.\n \n \n \n \n\n\n \n Vallat, B.; Webb, B.; Fayazi, M.; Voinea, S.; Tangmunarunkit, H.; Ganesan, S. J.; Lawson, C. L.; Westbrook, J. D.; Kesselman, C.; Sali, A.; and Berman, H. M.\n\n\n \n\n\n\n Acta Crystallographica Section D Structural Biology, 77(12): 1486–1496. December 2021.\n \n\n\n\n
\n\n\n\n \n \n \"NewPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{vallat_new_2021,\n\ttitle = {New system for archiving integrative structures},\n\tvolume = {77},\n\tissn = {2059-7983},\n\turl = {https://scripts.iucr.org/cgi-bin/paper?S2059798321010871},\n\tdoi = {10.1107/S2059798321010871},\n\tabstract = {Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.},\n\tnumber = {12},\n\turldate = {2022-01-14},\n\tjournal = {Acta Crystallographica Section D Structural Biology},\n\tauthor = {Vallat, Brinda and Webb, Benjamin and Fayazi, Maryam and Voinea, Serban and Tangmunarunkit, Hongsuda and Ganesan, Sai J. and Lawson, Catherine L. and Westbrook, John D. and Kesselman, Carl and Sali, Andrej and Berman, Helen M.},\n\tmonth = dec,\n\tyear = {2021},\n\tpages = {1486--1496},\n}\n\n
\n
\n\n\n
\n Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.\n
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\n  \n 2020\n \n \n (4)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types.\n \n \n \n \n\n\n \n Funk, C. C.; Casella, A. M.; Jung, S.; Richards, M. A.; Rodriguez, A.; Shannon, P.; Donovan-Maiye, R.; Heavner, B.; Chard, K.; Xiao, Y.; Glusman, G.; Ertekin-Taner, N.; Golde, T. E.; Toga, A.; Hood, L.; Van Horn, J. D.; Kesselman, C.; Foster, I.; Madduri, R.; Price, N. D.; and Ament, S. A.\n\n\n \n\n\n\n Cell Reports, 32(7): 108029. August 2020.\n \n\n\n\n
\n\n\n\n \n \n \"AtlasPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{funk_atlas_2020,\n\ttitle = {Atlas of {Transcription} {Factor} {Binding} {Sites} from {ENCODE} {DNase} {Hypersensitivity} {Data} across 27 {Tissue} {Types}},\n\tvolume = {32},\n\tissn = {22111247},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2211124720310147},\n\tdoi = {10.1016/j.celrep.2020.108029},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2022-01-22},\n\tjournal = {Cell Reports},\n\tauthor = {Funk, Cory C. and Casella, Alex M. and Jung, Segun and Richards, Matthew A. and Rodriguez, Alex and Shannon, Paul and Donovan-Maiye, Rory and Heavner, Ben and Chard, Kyle and Xiao, Yukai and Glusman, Gustavo and Ertekin-Taner, Nilufer and Golde, Todd E. and Toga, Arthur and Hood, Leroy and Van Horn, John D. and Kesselman, Carl and Foster, Ian and Madduri, Ravi and Price, Nathan D. and Ament, Seth A.},\n\tmonth = aug,\n\tyear = {2020},\n\tpages = {108029},\n}\n\n
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\n \n\n \n \n \n \n \n \n Towards Co-Evolution of Data-Centric Ecosystems.\n \n \n \n \n\n\n \n Schuler, R.; Czajkowski, K.; D'Arcy, M.; Tangmunarunkit, H.; and Kesselman, C.\n\n\n \n\n\n\n In 32nd International Conference on Scientific and Statistical Database Management, pages 1–12, Vienna Austria, July 2020. ACM\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{schuler_towards_2020,\n\taddress = {Vienna Austria},\n\ttitle = {Towards {Co}-{Evolution} of {Data}-{Centric} {Ecosystems}},\n\tisbn = {978-1-4503-8814-6},\n\turl = {https://dl.acm.org/doi/10.1145/3400903.3400908},\n\tdoi = {10.1145/3400903.3400908},\n\tlanguage = {en},\n\turldate = {2022-01-14},\n\tbooktitle = {32nd {International} {Conference} on {Scientific} and {Statistical} {Database} {Management}},\n\tpublisher = {ACM},\n\tauthor = {Schuler, Robert and Czajkowski, Karl and D'Arcy, Mike and Tangmunarunkit, Hongsuda and Kesselman, Carl},\n\tmonth = jul,\n\tyear = {2020},\n\tpages = {1--12},\n}\n\n
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\n \n\n \n \n \n \n \n \n An Open Ecosystem for Pervasive Use of Persistent Identifiers.\n \n \n \n \n\n\n \n Ananthakrishnan, R.; Chard, K.; D'Arcy, M.; Foster, I.; Kesselman, C.; McCollam, B.; Pruyne, J.; Rocca-Serra, P.; Schuler, R.; and Wagner, R.\n\n\n \n\n\n\n In Practice and Experience in Advanced Research Computing, pages 99–105, Portland OR USA, July 2020. ACM\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{ananthakrishnan_open_2020,\n\taddress = {Portland OR USA},\n\ttitle = {An {Open} {Ecosystem} for {Pervasive} {Use} of {Persistent} {Identifiers}},\n\tisbn = {978-1-4503-6689-2},\n\turl = {https://dl.acm.org/doi/10.1145/3311790.3396660},\n\tdoi = {10.1145/3311790.3396660},\n\tlanguage = {en},\n\turldate = {2022-01-14},\n\tbooktitle = {Practice and {Experience} in {Advanced} {Research} {Computing}},\n\tpublisher = {ACM},\n\tauthor = {Ananthakrishnan, Rachana and Chard, Kyle and D'Arcy, Mike and Foster, Ian and Kesselman, Carl and McCollam, Brendan and Pruyne, Jim and Rocca-Serra, Philippe and Schuler, Robert and Wagner, Rick},\n\tmonth = jul,\n\tyear = {2020},\n\tpages = {99--105},\n}\n\n
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\n \n\n \n \n \n \n \n \n FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research.\n \n \n \n \n\n\n \n Samuels, B. D.; Aho, R.; Brinkley, J. F.; Bugacov, A.; Feingold, E.; Fisher, S.; Gonzalez-Reiche, A. S.; Hacia, J. G.; Hallgrimsson, B.; Hansen, K.; Harris, M. P.; Ho, T.; Holmes, G.; Hooper, J. E.; Jabs, E. W.; Jones, K. L.; Kesselman, C.; Klein, O. D.; Leslie, E. J.; Li, H.; Liao, E. C.; Long, H.; Lu, N.; Maas, R. L.; Marazita, M. L.; Mohammed, J.; Prescott, S.; Schuler, R.; Selleri, L.; Spritz, R. A.; Swigut, T.; van Bakel, H.; Visel, A.; Welsh, I.; Williams, C.; Williams, T. J.; Wysocka, J.; Yuan, Y.; and Chai, Y.\n\n\n \n\n\n\n Development, 147(18): dev191213. September 2020.\n \n\n\n\n
\n\n\n\n \n \n \"FaceBasePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{samuels_facebase_2020,\n\ttitle = {{FaceBase} 3: analytical tools and {FAIR} resources for craniofacial and dental research},\n\tvolume = {147},\n\tissn = {1477-9129, 0950-1991},\n\tshorttitle = {{FaceBase} 3},\n\turl = {https://journals.biologists.com/dev/article/147/18/dev191213/225842/FaceBase-3-analytical-tools-and-FAIR-resources-for},\n\tdoi = {10.1242/dev.191213},\n\tabstract = {ABSTRACT\n            The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.},\n\tlanguage = {en},\n\tnumber = {18},\n\turldate = {2022-01-14},\n\tjournal = {Development},\n\tauthor = {Samuels, Bridget D. and Aho, Robert and Brinkley, James F. and Bugacov, Alejandro and Feingold, Eleanor and Fisher, Shannon and Gonzalez-Reiche, Ana S. and Hacia, Joseph G. and Hallgrimsson, Benedikt and Hansen, Karissa and Harris, Matthew P. and Ho, Thach-Vu and Holmes, Greg and Hooper, Joan E. and Jabs, Ethylin Wang and Jones, Kenneth L. and Kesselman, Carl and Klein, Ophir D. and Leslie, Elizabeth J. and Li, Hong and Liao, Eric C. and Long, Hannah and Lu, Na and Maas, Richard L. and Marazita, Mary L. and Mohammed, Jaaved and Prescott, Sara and Schuler, Robert and Selleri, Licia and Spritz, Richard A. and Swigut, Tomek and van Bakel, Harm and Visel, Axel and Welsh, Ian and Williams, Cristina and Williams, Trevor J. and Wysocka, Joanna and Yuan, Yuan and Chai, Yang},\n\tmonth = sep,\n\tyear = {2020},\n\tpages = {dev191213},\n}\n\n
\n
\n\n\n
\n ABSTRACT The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.\n
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\n  \n 2019\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n Computational Operations Research Exchange (Core): A Cyber-Infrastructure for Analytics.\n \n \n \n \n\n\n \n Deng, Y.; Kessleman, C.; Sen, S.; and Xu, J.\n\n\n \n\n\n\n In National Harbor, MD, USA, 2019. IEEE\n OCLC: 1200238240\n\n\n\n
\n\n\n\n \n \n \"ComputationalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{deng_computational_2019,\n\taddress = {National Harbor, MD, USA},\n\ttitle = {Computational {Operations} {Research} {Exchange} ({Core}): {A} {Cyber}-{Infrastructure} for {Analytics}},\n\tisbn = {978-1-72812-052-2 978-1-72813-283-9},\n\turl = {https://ieeexplore.ieee.org/servlet/opac?punumber=8977453},\n\tdoi = {https://doi.org/10.1109/WSC40007.2019.9004737},\n\tlanguage = {English},\n\turldate = {2022-01-21},\n\tpublisher = {IEEE},\n\tauthor = {Deng, Yunxiao and Kessleman, Carl and Sen, Suvrajeet and Xu, Jiajun},\n\tyear = {2019},\n\tnote = {OCLC: 1200238240},\n}\n\n
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\n \n\n \n \n \n \n \n \n Big Data Bags: A Scalable Packaging Format for Science.\n \n \n \n \n\n\n \n D'Arcy, M.; Chard, K.; Foster, I.; Kesselman, C.; Madduri, R.; Saint, N.; and Wagner, R.\n\n\n \n\n\n\n . July 2019.\n Publisher: Zenodo\n\n\n\n
\n\n\n\n \n \n \"BigPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{darcy_big_2019,\n\ttitle = {Big {Data} {Bags}: {A} {Scalable} {Packaging} {Format} for {Science}},\n\tcopyright = {Creative Commons Attribution 4.0 International, Open Access},\n\tshorttitle = {Big {Data} {Bags}},\n\turl = {https://zenodo.org/record/3338725},\n\tdoi = {10.5281/ZENODO.3338725},\n\tabstract = {The need to describe and exchange large and complex data underlies the vast majority of science conducted today. Such needs arise when downloading data from a repository, moving data between remote locations, exchanging data between collaborators, and even publishing data as part of the publication process. While such examples are common, it is surprisingly difficult to describe and exchange data, and it is even more difficult when datasets are large and span multiple storage locations. To address some of these challenges we proposed the Big Data Bag (BDBag) as a data packaging format for representing and describing complex, distributed, and large datasets. In this presentation, we outline the BDBag model and describe three scenarios in which it is currently being used},\n\turldate = {2022-01-14},\n\tauthor = {D'Arcy, Mike and Chard, Kyle and Foster, Ian and Kesselman, Carl and Madduri, Ravi and Saint, Nickolaus and Wagner, Rick},\n\tmonth = jul,\n\tyear = {2019},\n\tnote = {Publisher: Zenodo},\n}\n\n
\n
\n\n\n
\n The need to describe and exchange large and complex data underlies the vast majority of science conducted today. Such needs arise when downloading data from a repository, moving data between remote locations, exchanging data between collaborators, and even publishing data as part of the publication process. While such examples are common, it is surprisingly difficult to describe and exchange data, and it is even more difficult when datasets are large and span multiple storage locations. To address some of these challenges we proposed the Big Data Bag (BDBag) as a data packaging format for representing and describing complex, distributed, and large datasets. In this presentation, we outline the BDBag model and describe three scenarios in which it is currently being used\n
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\n \n\n \n \n \n \n \n \n Reproducible big data science: A case study in continuous FAIRness.\n \n \n \n \n\n\n \n Madduri, R.; Chard, K.; D’Arcy, M.; Jung, S. C.; Rodriguez, A.; Sulakhe, D.; Deutsch, E.; Funk, C.; Heavner, B.; Richards, M.; Shannon, P.; Glusman, G.; Price, N.; Kesselman, C.; and Foster, I.\n\n\n \n\n\n\n PLOS ONE, 14(4): e0213013. April 2019.\n \n\n\n\n
\n\n\n\n \n \n \"ReproduciblePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{madduri_reproducible_2019,\n\ttitle = {Reproducible big data science: {A} case study in continuous {FAIRness}},\n\tvolume = {14},\n\tissn = {1932-6203},\n\tshorttitle = {Reproducible big data science},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0213013},\n\tdoi = {10.1371/journal.pone.0213013},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-01-14},\n\tjournal = {PLOS ONE},\n\tauthor = {Madduri, Ravi and Chard, Kyle and D’Arcy, Mike and Jung, Segun C. and Rodriguez, Alexis and Sulakhe, Dinanath and Deutsch, Eric and Funk, Cory and Heavner, Ben and Richards, Matthew and Shannon, Paul and Glusman, Gustavo and Price, Nathan and Kesselman, Carl and Foster, Ian},\n\teditor = {Mehmood, Rashid},\n\tmonth = apr,\n\tyear = {2019},\n\tpages = {e0213013},\n}\n\n
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\n \n\n \n \n \n \n \n \n Toward FAIR Knowledge Turns in Bioinformatics.\n \n \n \n \n\n\n \n Schuler, R.; Bugacov, A.; Blow, M.; and Kesselman, C.\n\n\n \n\n\n\n In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 1240–1242, San Diego, CA, USA, November 2019. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"TowardPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{schuler_toward_2019,\n\taddress = {San Diego, CA, USA},\n\ttitle = {Toward {FAIR} {Knowledge} {Turns} in {Bioinformatics}},\n\tisbn = {978-1-72811-867-3},\n\turl = {https://ieeexplore.ieee.org/document/8982988/},\n\tdoi = {10.1109/BIBM47256.2019.8982988},\n\turldate = {2022-01-14},\n\tbooktitle = {2019 {IEEE} {International} {Conference} on {Bioinformatics} and {Biomedicine} ({BIBM})},\n\tpublisher = {IEEE},\n\tauthor = {Schuler, Robert and Bugacov, Alejandro and Blow, Matthew and Kesselman, Carl},\n\tmonth = nov,\n\tyear = {2019},\n\tpages = {1240--1242},\n}\n\n
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\n  \n 2018\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n ERMrest: a web service for collaborative data management.\n \n \n \n\n\n \n Czajkowski, K.; Kesselman, C.; Schuler, R. E.; and Tangmunarunkit, H.\n\n\n \n\n\n\n In Proceedings of the 30th International Conference on Scientific and Statistical Database Management, pages 1–12, Bozen-Bolzano Italy, July 2018. ACM\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{czajkowski_ermrest_2018,\n\taddress = {Bozen-Bolzano Italy},\n\ttitle = {{ERMrest}: a web service for collaborative data management},\n\tisbn = {978-1-4503-6505-5},\n\tshorttitle = {{ERMrest}},\n\tdoi = {10.1145/3221269.3222333},\n\tabstract = {The foundation of data oriented scientific collaboration is the abil- ity for participants to find, access and reuse data created during the course of an investigation, what has been referred to as the FAIR principles. In this paper, we describe ERMrest, a collaborative data management service that promotes data oriented collabora- tion by enabling FAIR data management throughout the data life cycle. ERMrest is a RESTful web service that promotes discovery and reuse by organizing diverse data assets into a dynamic entity relationship model. We present details on the design and implemen- tation of ERMrest, data on its performance and its use by a range of collaborations to accelerate and enhance their scientific output.},\n\tlanguage = {en},\n\turldate = {2022-01-29},\n\tbooktitle = {Proceedings of the 30th {International} {Conference} on {Scientific} and {Statistical} {Database} {Management}},\n\tpublisher = {ACM},\n\tauthor = {Czajkowski, Karl and Kesselman, Carl and Schuler, Robert E. and Tangmunarunkit, Hongsuda},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1--12},\n}\n\n
\n
\n\n\n
\n The foundation of data oriented scientific collaboration is the abil- ity for participants to find, access and reuse data created during the course of an investigation, what has been referred to as the FAIR principles. In this paper, we describe ERMrest, a collaborative data management service that promotes data oriented collabora- tion by enabling FAIR data management throughout the data life cycle. ERMrest is a RESTful web service that promotes discovery and reuse by organizing diverse data assets into a dynamic entity relationship model. We present details on the design and implemen- tation of ERMrest, data on its performance and its use by a range of collaborations to accelerate and enhance their scientific output.\n
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\n \n\n \n \n \n \n \n \n Towards an efficient and effective framework for the evolution of scientific databases.\n \n \n \n \n\n\n \n Schuler, R. E.; and Kesselman, C.\n\n\n \n\n\n\n In Proceedings of the 30th International Conference on Scientific and Statistical Database Management, pages 1–4, Bozen-Bolzano Italy, July 2018. ACM\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{schuler_towards_2018,\n\taddress = {Bozen-Bolzano Italy},\n\ttitle = {Towards an efficient and effective framework for the evolution of scientific databases},\n\tisbn = {978-1-4503-6505-5},\n\turl = {https://dl.acm.org/doi/10.1145/3221269.3221300},\n\tdoi = {10.1145/3221269.3221300},\n\tlanguage = {en},\n\turldate = {2022-01-15},\n\tbooktitle = {Proceedings of the 30th {International} {Conference} on {Scientific} and {Statistical} {Database} {Management}},\n\tpublisher = {ACM},\n\tauthor = {Schuler, Robert E. and Kesselman, Carl},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1--4},\n}\n\n
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\n \n\n \n \n \n \n \n Conserved and Divergent Features of Human and Mouse Kidney Organogenesis.\n \n \n \n\n\n \n Lindström, N.; McMahon, J.; Guo, J; Tran, T; Guo, Q; Rutledge, E; Parvez, R.; Saribekyan, G; Schuler, R.; Liao, C; Kim, A.; Abdelhalim, A; Ruffins, S.; Thornton, M.; Basking, L; Grubbs, B; Kesselman, C; and McMahon, A.\n\n\n \n\n\n\n Journal of the American Society of Nephrology. February 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{lindstrom_conserved_2018,\n\ttitle = {Conserved and {Divergent} {Features} of {Human} and {Mouse} {Kidney} {Organogenesis}.},\n\tdoi = {doi: 10.1681/ASN.2017080887},\n\tabstract = {Human kidney function is underpinned by approximately 1,000,000 nephrons, although the number varies substantially, and low nephron number is linked to disease. Human kidney development initiates around 4 weeks of gestation and ends around 34-37 weeks of gestation. Over this period, a reiterative inductive process establishes the nephron complement. Studies have provided insightful anatomic descriptions of human kidney development, but the limited histologic views are not readily accessible to a broad audience. In this first paper in a series providing comprehensive insight into human kidney formation, we examined human kidney development in 135 anonymously donated human kidney specimens. We documented kidney development at a macroscopic and cellular level through histologic analysis, RNA in situ hybridization, immunofluorescence studies, and transcriptional profiling, contrasting human development (4-23 weeks) with mouse development at selected stages (embryonic day 15.5 and postnatal day 2). The high-resolution histologic interactive atlas of human kidney organogenesis generated can be viewed at the GUDMAP database (www.gudmap.org) together with three-dimensional reconstructions of key components of the data herein. At the anatomic level, human and mouse kidney development differ in timing, scale, and global features such as lobe formation and progenitor niche organization. The data also highlight differences in molecular and cellular features, including the expression and cellular distribution of anchor gene markers used to identify key cell types in mouse kidney studies. These data will facilitate and inform in vitro efforts to generate human kidney structures and comparative functional analyses across mammalian species.},\n\tjournal = {Journal of the American Society of Nephrology},\n\tauthor = {Lindström, NO and McMahon, JA and Guo, J and Tran, T and Guo, Q and Rutledge, E and Parvez, RK and Saribekyan, G and Schuler, RE and Liao, C and Kim, AD and Abdelhalim, A and Ruffins, SW and Thornton, ME and Basking, L and Grubbs, B and Kesselman, C and McMahon, AP},\n\tmonth = feb,\n\tyear = {2018},\n}\n\n
\n
\n\n\n
\n Human kidney function is underpinned by approximately 1,000,000 nephrons, although the number varies substantially, and low nephron number is linked to disease. Human kidney development initiates around 4 weeks of gestation and ends around 34-37 weeks of gestation. Over this period, a reiterative inductive process establishes the nephron complement. Studies have provided insightful anatomic descriptions of human kidney development, but the limited histologic views are not readily accessible to a broad audience. In this first paper in a series providing comprehensive insight into human kidney formation, we examined human kidney development in 135 anonymously donated human kidney specimens. We documented kidney development at a macroscopic and cellular level through histologic analysis, RNA in situ hybridization, immunofluorescence studies, and transcriptional profiling, contrasting human development (4-23 weeks) with mouse development at selected stages (embryonic day 15.5 and postnatal day 2). The high-resolution histologic interactive atlas of human kidney organogenesis generated can be viewed at the GUDMAP database (www.gudmap.org) together with three-dimensional reconstructions of key components of the data herein. At the anatomic level, human and mouse kidney development differ in timing, scale, and global features such as lobe formation and progenitor niche organization. The data also highlight differences in molecular and cellular features, including the expression and cellular distribution of anchor gene markers used to identify key cell types in mouse kidney studies. These data will facilitate and inform in vitro efforts to generate human kidney structures and comparative functional analyses across mammalian species.\n
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\n  \n 2017\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n Experiences with DERIVA: An Asset Management Platform for Accelerating eScience.\n \n \n \n \n\n\n \n Bugacov, A.; Czajkowski, K.; Kesselman, C.; Kumar, A.; Schuler, R. E.; and Tangmunarunkit, H.\n\n\n \n\n\n\n In 2017 IEEE 13th International Conference on e-Science (e-Science), pages 79–88, Auckland, October 2017. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"ExperiencesPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{bugacov_experiences_2017,\n\taddress = {Auckland},\n\ttitle = {Experiences with {DERIVA}: {An} {Asset} {Management} {Platform} for {Accelerating} {eScience}},\n\tisbn = {978-1-5386-2686-3},\n\tshorttitle = {Experiences with {DERIVA}},\n\turl = {https://ieeexplore.ieee.org/document/8109125/},\n\tdoi = {10.1109/eScience.2017.20},\n\turldate = {2022-01-15},\n\tbooktitle = {2017 {IEEE} 13th {International} {Conference} on e-{Science} (e-{Science})},\n\tpublisher = {IEEE},\n\tauthor = {Bugacov, Alejandro and Czajkowski, Karl and Kesselman, Carl and Kumar, Anoop and Schuler, Robert E. and Tangmunarunkit, Hongsuda},\n\tmonth = oct,\n\tyear = {2017},\n\tpages = {79--88},\n}\n\n
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\n \n\n \n \n \n \n \n \n ERMRest: A Collaborative Data Catalog with Fine Grain Access Control.\n \n \n \n \n\n\n \n Czajkowski, K.; Kesselman, C.; and Schuler, R.\n\n\n \n\n\n\n In 2017 IEEE 13th International Conference on e-Science (e-Science), pages 510–517, Auckland, October 2017. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"ERMRest:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{czajkowski_ermrest_2017,\n\taddress = {Auckland},\n\ttitle = {{ERMRest}: {A} {Collaborative} {Data} {Catalog} with {Fine} {Grain} {Access} {Control}},\n\tisbn = {978-1-5386-2686-3},\n\tshorttitle = {{ERMRest}},\n\turl = {http://ieeexplore.ieee.org/document/8109188/},\n\tdoi = {10.1109/eScience.2017.83},\n\turldate = {2022-01-15},\n\tbooktitle = {2017 {IEEE} 13th {International} {Conference} on e-{Science} (e-{Science})},\n\tpublisher = {IEEE},\n\tauthor = {Czajkowski, Karl and Kesselman, Carl and Schuler, Robert},\n\tmonth = oct,\n\tyear = {2017},\n\tpages = {510--517},\n}\n\n
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\n \n\n \n \n \n \n \n \n Ambient and laboratory evaluation of a low-cost particulate matter sensor.\n \n \n \n \n\n\n \n Kelly, K. E.; Whitaker, J.; Petty, A.; Widmer, C.; Dybwad, A.; Sleeth, D.; Martin, R.; and Butterfield, A.\n\n\n \n\n\n\n Environmental Pollution, 221: 491 – 500. February 2017.\n \n\n\n\n
\n\n\n\n \n \n \"AmbientPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{kelly_ambient_2017,\n\ttitle = {Ambient and laboratory evaluation of a low-cost particulate matter sensor},\n\tvolume = {221},\n\tissn = {0269-7491},\n\turl = {http://prisms-study.org/publications/KK_EnvironmentalPollution_2017.pdf},\n\tdoi = {https://doi.org/10.1016/j.envpol.2016.12.039},\n\tabstract = {Low-cost, light-scattering-based particulate matter (PM) sensors are becoming more widely available and are being increasingly deployed in ambient and indoor environments because of their low cost and ability to provide high spatial and temporal resolution PM information. Researchers have begun to evaluate some of these sensors under laboratory and environmental conditions. In this study, a low-cost, particulate matter sensor (Plantower PMS 1003/3003) used by a community air-quality network is evaluated in a controlled wind-tunnel environment and in the ambient environment during several winter-time, cold-pool events that are associated with high ambient levels of PM. In the wind-tunnel, the PMS sensor performance is compared to two research-grade, light-scattering instruments, and in the ambient tests, the sensor performance is compared to two federal equivalent (one tapered element oscillating microbalance and one beta attenuation monitor) and gravimetric federal reference methods (FEMs/FRMs) as well as one research-grade instrument (GRIMM). The PMS sensor response correlates well with research-grade instruments in the wind-tunnel tests, and its response is linear over the concentration range tested (200–850 μg/m3). In the ambient tests, this PM sensor correlates better with gravimetric methods than previous studies with correlation coefficients of 0.88. However additional measurements under a variety of ambient conditions are needed. Although the PMS sensor correlated as well as the research-grade instrument to the FRM/FEMs in ambient conditions, its response varies with particle properties to a much greater degree than the research-grade instrument. In addition, the PMS sensors overestimate ambient PM concentrations and begin to exhibit a non-linear response when PM2.5 concentrations exceed 40 μg/m3. These results have important implications for communicating results from low-cost sensor networks, and they highlight the importance of using an appropriate correction factor for the target environmental conditions if the user wants to compare the results to FEM/FRMs.},\n\tjournal = {Environmental Pollution},\n\tauthor = {Kelly, K. E. and Whitaker, J. and Petty, A. and Widmer, C. and Dybwad, A. and Sleeth, D. and Martin, R. and Butterfield, A.},\n\tmonth = feb,\n\tyear = {2017},\n\tkeywords = {Air quality, Cold-air pool, Low-cost sensors, Particulate matter},\n\tpages = {491 -- 500},\n}\n\n
\n
\n\n\n
\n Low-cost, light-scattering-based particulate matter (PM) sensors are becoming more widely available and are being increasingly deployed in ambient and indoor environments because of their low cost and ability to provide high spatial and temporal resolution PM information. Researchers have begun to evaluate some of these sensors under laboratory and environmental conditions. In this study, a low-cost, particulate matter sensor (Plantower PMS 1003/3003) used by a community air-quality network is evaluated in a controlled wind-tunnel environment and in the ambient environment during several winter-time, cold-pool events that are associated with high ambient levels of PM. In the wind-tunnel, the PMS sensor performance is compared to two research-grade, light-scattering instruments, and in the ambient tests, the sensor performance is compared to two federal equivalent (one tapered element oscillating microbalance and one beta attenuation monitor) and gravimetric federal reference methods (FEMs/FRMs) as well as one research-grade instrument (GRIMM). The PMS sensor response correlates well with research-grade instruments in the wind-tunnel tests, and its response is linear over the concentration range tested (200–850 μg/m3). In the ambient tests, this PM sensor correlates better with gravimetric methods than previous studies with correlation coefficients of 0.88. However additional measurements under a variety of ambient conditions are needed. Although the PMS sensor correlated as well as the research-grade instrument to the FRM/FEMs in ambient conditions, its response varies with particle properties to a much greater degree than the research-grade instrument. In addition, the PMS sensors overestimate ambient PM concentrations and begin to exhibit a non-linear response when PM2.5 concentrations exceed 40 μg/m3. These results have important implications for communicating results from low-cost sensor networks, and they highlight the importance of using an appropriate correction factor for the target environmental conditions if the user wants to compare the results to FEM/FRMs.\n
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\n \n\n \n \n \n \n \n \n (Re)Building a Kidney.\n \n \n \n \n\n\n \n Oxburgh, L; Carroll, T.; Cleaver, O; Gossett, D.; Hoshizaki, D.; Hubbell, J.; Humphreys, B.; Jain, S; Jensen, J; Kaplan, D.; Kesselman, C; Ketchum, C.; Little, M.; McMahon, A.; Shankland, S.; Spence, J.; Valerius, M.; Wertheim, J.; Wessely, O; Zheng, Y; and Drummond, I.\n\n\n \n\n\n\n Journal of the American Society of Nephrology, 28(5): 1370–1378. May 2017.\n \n\n\n\n
\n\n\n\n \n \n \"(Re)BuildingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{oxburgh_rebuilding_2017,\n\ttitle = {({Re}){Building} a {Kidney}.},\n\tvolume = {28},\n\turl = {https://www.rebuildingakidney.org/publications/RBK_Manuscript.pdf},\n\tdoi = {10.1681/ASN.2016101077},\n\tabstract = {(Re)Building a Kidney is a National Institute of Diabetes and Digestive and Kidney Diseases-led consortium to optimize approaches for the isolation, expansion, and differentiation of appropriate kidney cell types and the integration of these cells into complex structures that replicate human kidney function. The ultimate goals of the consortium are two-fold: to develop and implement strategies for in vitro engineering of replacement kidney tissue, and to devise strategies to stimulate regeneration of nephrons in situ to restore failing kidney function. Projects within the consortium will answer fundamental questions regarding human gene expression in the developing kidney, essential signaling crosstalk between distinct cell types of the developing kidney, how to derive the many cell types of the kidney through directed differentiation of human pluripotent stem cells, which bioengineering or scaffolding strategies have the most potential for kidney tissue formation, and basic parameters of the regenerative response to injury. As these projects progress, the consortium will incorporate systematic investigations in physiologic function of in vitro and in vivo differentiated kidney tissue, strategies for engraftment in experimental animals, and development of therapeutic approaches to activate innate reparative responses.},\n\tnumber = {5},\n\tjournal = {Journal of the American Society of Nephrology},\n\tauthor = {Oxburgh, L and Carroll, TJ and Cleaver, O and Gossett, DR and Hoshizaki, DK and Hubbell, JA and Humphreys, BD and Jain, S and Jensen, J and Kaplan, DL and Kesselman, C and Ketchum, CJ and Little, MH and McMahon, AP and Shankland, SJ and Spence, JR and Valerius, MT and Wertheim, JA and Wessely, O and Zheng, Y and Drummond, IA},\n\tmonth = may,\n\tyear = {2017},\n\tpages = {1370--1378},\n}\n\n
\n
\n\n\n
\n (Re)Building a Kidney is a National Institute of Diabetes and Digestive and Kidney Diseases-led consortium to optimize approaches for the isolation, expansion, and differentiation of appropriate kidney cell types and the integration of these cells into complex structures that replicate human kidney function. The ultimate goals of the consortium are two-fold: to develop and implement strategies for in vitro engineering of replacement kidney tissue, and to devise strategies to stimulate regeneration of nephrons in situ to restore failing kidney function. Projects within the consortium will answer fundamental questions regarding human gene expression in the developing kidney, essential signaling crosstalk between distinct cell types of the developing kidney, how to derive the many cell types of the kidney through directed differentiation of human pluripotent stem cells, which bioengineering or scaffolding strategies have the most potential for kidney tissue formation, and basic parameters of the regenerative response to injury. As these projects progress, the consortium will incorporate systematic investigations in physiologic function of in vitro and in vivo differentiated kidney tissue, strategies for engraftment in experimental animals, and development of therapeutic approaches to activate innate reparative responses.\n
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\n  \n 2016\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets.\n \n \n \n \n\n\n \n Chard, K.; D'Arcy, M.; Heavner, B.; Foster, I.; Kesselman, C.; Madduri, R.; Rodriguez, A.; Soiland-Reyes, S.; Goble, C.; Clark, K.; Deutsch, E. W.; Dinov, I.; Price, N.; and Toga, A.\n\n\n \n\n\n\n In 2016 IEEE International Conference on Big Data (Big Data), pages 319–328, Washington DC,USA, December 2016. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"I'llPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{chard_ill_2016,\n\taddress = {Washington DC,USA},\n\ttitle = {I'll take that to go: {Big} data bags and minimal identifiers for exchange of large, complex datasets},\n\tisbn = {978-1-4673-9005-7},\n\tshorttitle = {I'll take that to go},\n\turl = {http://ieeexplore.ieee.org/document/7840618/},\n\tdoi = {10.1109/BigData.2016.7840618},\n\turldate = {2023-12-08},\n\tbooktitle = {2016 {IEEE} {International} {Conference} on {Big} {Data} ({Big} {Data})},\n\tpublisher = {IEEE},\n\tauthor = {Chard, Kyle and D'Arcy, Mike and Heavner, Ben and Foster, Ian and Kesselman, Carl and Madduri, Ravi and Rodriguez, Alexis and Soiland-Reyes, Stian and Goble, Carole and Clark, Kristi and Deutsch, Eric W. and Dinov, Ivo and Price, Nathan and Toga, Arthur},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {319--328},\n}\n\n
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\n \n\n \n \n \n \n \n \n Accelerating Data-driven Discovery with Scientific Asset Management.\n \n \n \n \n\n\n \n Schuler, R.; Kesselman, C.; and Czajkowski, K.\n\n\n \n\n\n\n In Proceedings of the 12th IEEE International Conference on eScience, 2016. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"AcceleratingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{schuler_accelerating_2016,\n\ttitle = {Accelerating {Data}-driven {Discovery} with {Scientific} {Asset} {Management}},\n\turl = {https://www.zotero.org/crisaless/collections/SP6RMP59/items/8MC3BI7S/attachment/3FEQG8G8/reader},\n\tabstract = {Current approaches for\nment have failed to keep pace with the needs of increasingly data-intensive science. The overhead and burden of managing data in complex discovery processes, involving experimental protocols with numerous data-producing and computational steps, has become the gating factor that determines the pace of discovery. The lack of comprehensive systems to capture, manage, organize and retrieve data throughout the discovery life cycle leads to significant overheads on scientists time and effort, reduced productivity, lack of reproducibility, and an absence of data sharing.\nIn “creative fields” like digital photography and music, digi- tal asset management (DAM) systems for capturing, managing, curating and consuming digital assets like photos and audio recordings, have fundamentally transformed how these data are used. While asset management has not taken hold in eScience applications, we believe that transformation similar to that observed in the creative space could be achieved in scientific domains if appropriate ecosystems of asset management tools existed, tools to capture, manage, and curate data throughout the scientific discovery process. We introduce a framework and infrastructure for asset management in eScience and present initial results from its usage in active research use cases.},\n\tbooktitle = {Proceedings of the 12th {IEEE} {International} {Conference} on {eScience}},\n\tpublisher = {IEEE},\n\tauthor = {Schuler, Robert and Kesselman, Carl and Czajkowski, Karl},\n\tyear = {2016},\n}\n\n
\n
\n\n\n
\n Current approaches for ment have failed to keep pace with the needs of increasingly data-intensive science. The overhead and burden of managing data in complex discovery processes, involving experimental protocols with numerous data-producing and computational steps, has become the gating factor that determines the pace of discovery. The lack of comprehensive systems to capture, manage, organize and retrieve data throughout the discovery life cycle leads to significant overheads on scientists time and effort, reduced productivity, lack of reproducibility, and an absence of data sharing. In “creative fields” like digital photography and music, digi- tal asset management (DAM) systems for capturing, managing, curating and consuming digital assets like photos and audio recordings, have fundamentally transformed how these data are used. While asset management has not taken hold in eScience applications, we believe that transformation similar to that observed in the creative space could be achieved in scientific domains if appropriate ecosystems of asset management tools existed, tools to capture, manage, and curate data throughout the scientific discovery process. We introduce a framework and infrastructure for asset management in eScience and present initial results from its usage in active research use cases.\n
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\n \n\n \n \n \n \n \n \n ERMrest: an entity-relationship data storage service for web-based, data-oriented collaboration.\n \n \n \n \n\n\n \n Czajkowski, K.; Kesselman, C.; Schuler, R.; and Tangmunarunkit, H.\n\n\n \n\n\n\n . 2016.\n Publisher: arXiv Version Number: 1\n\n\n\n
\n\n\n\n \n \n \"ERMrest:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{czajkowski_ermrest_2016,\n\ttitle = {{ERMrest}: an entity-relationship data storage service for web-based, data-oriented collaboration},\n\tcopyright = {arXiv.org perpetual, non-exclusive license},\n\tshorttitle = {{ERMrest}},\n\turl = {https://arxiv.org/abs/1610.06044},\n\tdoi = {10.48550/ARXIV.1610.06044},\n\tabstract = {Scientific discovery is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. While the details vary from domain to domain, these data often consist of diverse digital assets (e.g. image files, sequence data, or simulation outputs) that are organized with complex relationships and context which may evolve over the course of an investigation. In addition, discovery is often collaborative, such that sharing of the data and its organizational context is highly desirable. Common systems for managing file or asset metadata hide their inherent relational structures, while traditional relational database systems do not extend to the distributed collaborative environment often seen in scientific investigations. To address these issues, we introduce ERMrest, a collaborative data management service which allows general entity-relationship modeling of metadata manipulated by RESTful access methods. We present the design criteria, architecture, and service implementation, as well as describe an ecosystem of tools and services that we have created to integrate metadata into an end-to-end scientific data life cycle. ERMrest has been deployed to hundreds of users across multiple scientific research communities and projects. We present two representative use cases: an international consortium and an early-phase, multidisciplinary research project.},\n\turldate = {2023-12-08},\n\tauthor = {Czajkowski, Karl and Kesselman, Carl and Schuler, Robert and Tangmunarunkit, Hongsuda},\n\tyear = {2016},\n\tnote = {Publisher: arXiv\nVersion Number: 1},\n\tkeywords = {Databases (cs.DB), Digital Libraries (cs.DL), Distributed, Parallel, and Cluster Computing (cs.DC), FOS: Computer and information sciences, Human-Computer Interaction (cs.HC)},\n}\n\n
\n
\n\n\n
\n Scientific discovery is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. While the details vary from domain to domain, these data often consist of diverse digital assets (e.g. image files, sequence data, or simulation outputs) that are organized with complex relationships and context which may evolve over the course of an investigation. In addition, discovery is often collaborative, such that sharing of the data and its organizational context is highly desirable. Common systems for managing file or asset metadata hide their inherent relational structures, while traditional relational database systems do not extend to the distributed collaborative environment often seen in scientific investigations. To address these issues, we introduce ERMrest, a collaborative data management service which allows general entity-relationship modeling of metadata manipulated by RESTful access methods. We present the design criteria, architecture, and service implementation, as well as describe an ecosystem of tools and services that we have created to integrate metadata into an end-to-end scientific data life cycle. ERMrest has been deployed to hundreds of users across multiple scientific research communities and projects. We present two representative use cases: an international consortium and an early-phase, multidisciplinary research project.\n
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\n \n\n \n \n \n \n \n \n MultiCellDS: a standard and a community for sharing multicellular data.\n \n \n \n \n\n\n \n Friedman, S. H.; Anderson, A. R. A.; Bortz, D. M.; Fletcher, A. G.; Frieboes, H. B.; Ghaffarizadeh, A.; Grimes, D. R.; Hawkins-Daarud, A.; Hoehme, S.; Juarez, E. F.; Kesselman, C.; Merks, R. M.; Mumenthaler, S. M.; Newton, P. K.; Norton, K.; Rawat, R.; Rockne, R. C.; Ruderman, D.; Scott, J.; Sindi, S. S.; Sparks, J. L.; Swanson, K.; Agus, D. B.; and Macklin, P.\n\n\n \n\n\n\n Technical Report Systems Biology, December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MultiCellDS:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@techreport{friedman_multicellds_2016,\n\ttype = {preprint},\n\ttitle = {{MultiCellDS}: a standard and a community for sharing multicellular data},\n\tshorttitle = {{MultiCellDS}},\n\turl = {http://biorxiv.org/lookup/doi/10.1101/090696},\n\tabstract = {Abstract\n          Cell biology is increasingly focused on cellular heterogeneity and multicellular systems. To make the fullest use of experimental, clinical, and computational efforts, we need standardized data formats, community-curated “public data libraries”, and tools to combine and analyze shared data. To address these needs, our multidisciplinary community created MultiCellDS (MultiCellular Data Standard): an extensible standard, a library of digital cell lines and tissue snapshots, and support software. With the help of experimentalists, clinicians, modelers, and data and library scientists, we can grow this seed into a community-owned ecosystem of shared data and tools, to the benefit of basic science, engineering, and human health.},\n\tlanguage = {en},\n\turldate = {2022-01-22},\n\tinstitution = {Systems Biology},\n\tauthor = {Friedman, Samuel H. and Anderson, Alexander R. A. and Bortz, David M. and Fletcher, Alexander G. and Frieboes, Hermann B. and Ghaffarizadeh, Ahmadreza and Grimes, David Robert and Hawkins-Daarud, Andrea and Hoehme, Stefan and Juarez, Edwin F. and Kesselman, Carl and Merks, Roeland M.H. and Mumenthaler, Shannon M. and Newton, Paul K. and Norton, Kerri-Ann and Rawat, Rishi and Rockne, Russell C. and Ruderman, Daniel and Scott, Jacob and Sindi, Suzanne S. and Sparks, Jessica L. and Swanson, Kristin and Agus, David B. and Macklin, Paul},\n\tmonth = dec,\n\tyear = {2016},\n\tdoi = {10.1101/090696},\n}\n\n
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\n\n\n
\n Abstract Cell biology is increasingly focused on cellular heterogeneity and multicellular systems. To make the fullest use of experimental, clinical, and computational efforts, we need standardized data formats, community-curated “public data libraries”, and tools to combine and analyze shared data. To address these needs, our multidisciplinary community created MultiCellDS (MultiCellular Data Standard): an extensible standard, a library of digital cell lines and tissue snapshots, and support software. With the help of experimentalists, clinicians, modelers, and data and library scientists, we can grow this seed into a community-owned ecosystem of shared data and tools, to the benefit of basic science, engineering, and human health.\n
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\n \n\n \n \n \n \n \n The FaceBase Consortium: a comprehensive resource for craniofacial researchers.\n \n \n \n\n\n \n Brinkley, J.; Fisher, S; Harris, M.; Holmes, G; Hooper, J.; Jabs, E.; Jones, K.; Kesselman, C; Klein, O.; Maas, R.; Marazita, M.; Selleri, L; Spritz, R.; van Bakel, H; Visel, A; Williams, T.; Wysocka, J; Consortium, F.; and Chai, Y\n\n\n \n\n\n\n Development, 143(14): 2677–88. July 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{brinkley_facebase_2016,\n\ttitle = {The {FaceBase} {Consortium}: a comprehensive resource for craniofacial researchers.},\n\tvolume = {143},\n\tdoi = {10.1242/dev.135434},\n\tabstract = {The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research, National Institutes of Health, is designed to accelerate understanding of craniofacial developmental biology by generating comprehensive data resources to empower the research community, exploring high-throughput technology, fostering new scientific collaborations among researchers and human/computer interactions, facilitating hypothesis-driven research and translating science into improved health care to benefit patients. The resources generated by the FaceBase projects include a number of dynamic imaging modalities, genome-wide association studies, software tools for analyzing human facial abnormalities, detailed phenotyping, anatomical and molecular atlases, global and specific gene expression patterns, and transcriptional profiling over the course of embryonic and postnatal development in animal models and humans. The integrated data visualization tools, faceted search infrastructure, and curation provided by the FaceBase Hub offer flexible and intuitive ways to interact with these multidisciplinary data. In parallel, the datasets also offer unique opportunities for new collaborations and training for researchers coming into the field of craniofacial studies. Here, we highlight the focus of each spoke project and the integration of datasets contributed by the spokes to facilitate craniofacial research.},\n\tnumber = {14},\n\tjournal = {Development},\n\tauthor = {Brinkley, JF and Fisher, S and Harris, MP and Holmes, G and Hooper, JE and Jabs, EW and Jones, KL and Kesselman, C and Klein, OD and Maas, RL and Marazita, ML and Selleri, L and Spritz, RA and van Bakel, H and Visel, A and Williams, TJ and Wysocka, J and FaceBase Consortium and Chai, Y},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {2677--88},\n}\n\n
\n
\n\n\n
\n The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research, National Institutes of Health, is designed to accelerate understanding of craniofacial developmental biology by generating comprehensive data resources to empower the research community, exploring high-throughput technology, fostering new scientific collaborations among researchers and human/computer interactions, facilitating hypothesis-driven research and translating science into improved health care to benefit patients. The resources generated by the FaceBase projects include a number of dynamic imaging modalities, genome-wide association studies, software tools for analyzing human facial abnormalities, detailed phenotyping, anatomical and molecular atlases, global and specific gene expression patterns, and transcriptional profiling over the course of embryonic and postnatal development in animal models and humans. The integrated data visualization tools, faceted search infrastructure, and curation provided by the FaceBase Hub offer flexible and intuitive ways to interact with these multidisciplinary data. In parallel, the datasets also offer unique opportunities for new collaborations and training for researchers coming into the field of craniofacial studies. Here, we highlight the focus of each spoke project and the integration of datasets contributed by the spokes to facilitate craniofacial research.\n
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\n \n\n \n \n \n \n \n Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-source and Incomplete Observations.\n \n \n \n\n\n \n Dinov, I. D.; Heavner, B.; Tang, M.; Glusman, G.; Chard, K.; Darcy, M.; Madduri, R.; Pa, J.; Spino, C.; Kesselman, C.; and others\n\n\n \n\n\n\n , 11(8): e0157077. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{dinov_predictive_2016,\n\ttitle = {Predictive {Big} {Data} {Analytics}: {A} {Study} of {Parkinson}’s {Disease} {Using} {Large}, {Complex}, {Heterogeneous}, {Incongruent}, {Multi}-source and {Incomplete} {Observations}},\n\tvolume = {11},\n\tnumber = {8},\n\tauthor = {Dinov, Ivo D. and Heavner, Ben and Tang, Ming and Glusman, Gustavo and Chard, Kyle and Darcy, Mike and Madduri, Ravi and Pa, Judy and Spino, Cathie and Kesselman, Carl and {others}},\n\tyear = {2016},\n\tpages = {e0157077},\n}\n\n
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\n  \n 2015\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Data Centric Discovery with a Data-Oriented Architecture.\n \n \n \n \n\n\n \n Schuler, R.; Kesselman, C.; and Czajkowski, K.\n\n\n \n\n\n\n In Proceedings of the 1st Workshop on The Science of Cyberinfrastructure: Research, Experience, Applications and Models, pages 37–44, Portland Oregon USA, June 2015. ACM\n \n\n\n\n
\n\n\n\n \n \n \"DataPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{schuler_data_2015,\n\taddress = {Portland Oregon USA},\n\ttitle = {Data {Centric} {Discovery} with a {Data}-{Oriented} {Architecture}},\n\tisbn = {978-1-4503-3566-9},\n\turl = {https://dl.acm.org/doi/10.1145/2753524.2753532},\n\tdoi = {10.1145/2753524.2753532},\n\tlanguage = {en},\n\turldate = {2022-01-15},\n\tbooktitle = {Proceedings of the 1st {Workshop} on {The} {Science} of {Cyberinfrastructure}: {Research}, {Experience}, {Applications} and {Models}},\n\tpublisher = {ACM},\n\tauthor = {Schuler, Robert and Kesselman, Carl and Czajkowski, Karl},\n\tmonth = jun,\n\tyear = {2015},\n\tpages = {37--44},\n}\n\n
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\n \n\n \n \n \n \n \n A System to Build Distributed Multivariate Models and Manage Disparate Data Sharing Policies: Implementation in the Scalable National Network for Effectiveness Research.\n \n \n \n\n\n \n Meeker, D.; Jiang, X.; Matheny, M. E.; Farcas, C.; D’Arcy, M.; Pearlman, L.; Nookala, L.; Day, M. E.; Kim, K. K.; Kim, H.; and others\n\n\n \n\n\n\n , 22(6): 1187–1195. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{meeker_system_2015,\n\ttitle = {A {System} to {Build} {Distributed} {Multivariate} {Models} and {Manage} {Disparate} {Data} {Sharing} {Policies}: {Implementation} in the {Scalable} {National} {Network} for {Effectiveness} {Research}},\n\tvolume = {22},\n\tnumber = {6},\n\tauthor = {Meeker, Daniella and Jiang, Xiaoqian and Matheny, Michael E. and Farcas, Claudiu and D’Arcy, Michel and Pearlman, Laura and Nookala, Lavanya and Day, Michele E. and Kim, Katherine K. and Kim, Hyeoneui and {others}},\n\tyear = {2015},\n\tpages = {1187--1195},\n}\n\n
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\n \n\n \n \n \n \n \n Big Biomedical Data As the Key Resource for Discovery Science.\n \n \n \n\n\n \n Toga, A. W.; Foster, I.; Kesselman, C.; Madduri, R.; Chard, K.; Deutsch, E. W.; Price, N. D.; Glusman, G.; Heavner, B. D.; Dinov, I. D.; and others\n\n\n \n\n\n\n ,ocv077. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{toga_big_2015,\n\ttitle = {Big {Biomedical} {Data} {As} the {Key} {Resource} for {Discovery} {Science}},\n\tauthor = {Toga, Arthur W. and Foster, Ian and Kesselman, Carl and Madduri, Ravi and Chard, Kyle and Deutsch, Eric W. and Price, Nathan D. and Glusman, Gustavo and Heavner, Benjamin D. and Dinov, Ivo D. and {others}},\n\tyear = {2015},\n\tpages = {ocv077},\n}\n\n
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\n  \n 2014\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Digital asset management for heterogeneous biomedical data in an era of data-intensive science.\n \n \n \n \n\n\n \n Schuler, R. E.; Kesselman, C.; and Czajkowski, K.\n\n\n \n\n\n\n In 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 588–592, Belfast, United Kingdom, November 2014. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"DigitalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{schuler_digital_2014,\n\taddress = {Belfast, United Kingdom},\n\ttitle = {Digital asset management for heterogeneous biomedical data in an era of data-intensive science},\n\tisbn = {978-1-4799-5669-2},\n\turl = {http://ieeexplore.ieee.org/document/6999226/},\n\tdoi = {10.1109/BIBM.2014.6999226},\n\turldate = {2022-01-15},\n\tbooktitle = {2014 {IEEE} {International} {Conference} on {Bioinformatics} and {Biomedicine} ({BIBM})},\n\tpublisher = {IEEE},\n\tauthor = {Schuler, Robert E. and Kesselman, Carl and Czajkowski, Karl},\n\tmonth = nov,\n\tyear = {2014},\n\tpages = {588--592},\n}\n\n
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\n  \n 2013\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n A Physical Sciences Network Characterization of Non-tumorigenic and Metastatic Cells.\n \n \n \n\n\n \n Agus, D. B.; Alexander, J. F.; Arap, W.; Ashili, S.; Aslan, J. E.; Austin, R. H.; Backman, V.; Bethel, K. J.; Bonneau, R.; Chen, W. C.; and others\n\n\n \n\n\n\n , 3. 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{agus_physical_2013,\n\ttitle = {A {Physical} {Sciences} {Network} {Characterization} of {Non}-tumorigenic and {Metastatic} {Cells}},\n\tvolume = {3},\n\tauthor = {Agus, David B. and Alexander, Jenolyn F. and Arap, Wadih and Ashili, Shashanka and Aslan, Joseph E. and Austin, Robert H. and Backman, Vadim and Bethel, Kelly J. and Bonneau, Richard and Chen, Wei Chiang and {others}},\n\tyear = {2013},\n}\n\n
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\n  \n 2012\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n A System Architecture for Sharing De-identified, Research-ready Brain Scans and Health Information across Clinical Imaging Centers.\n \n \n \n\n\n \n Chervenak, A. L.; van Erp, T. G. M.; Kesselman, C.; D’Arcy, M.; Sobell, J.; Keator, D.; Dahm, L.; Murry, J.; Law, M.; Hasso, A.; and others\n\n\n \n\n\n\n , 175: 19. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chervenak_system_2012,\n\ttitle = {A {System} {Architecture} for {Sharing} {De}-identified, {Research}-ready {Brain} {Scans} and {Health} {Information} across {Clinical} {Imaging} {Centers}},\n\tvolume = {175},\n\tauthor = {Chervenak, Ann L. and van Erp, Theo G. M. and Kesselman, Carl and D’Arcy, Mike and Sobell, Janet and Keator, David and Dahm, Lisa and Murry, Jim and Law, Meng and Hasso, Anton and {others}},\n\tyear = {2012},\n\tpages = {19},\n}\n\n
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\n  \n 2010\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n The History of the Grid.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n , 20(21): 22. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{foster_history_2010,\n\ttitle = {The {History} of the {Grid}},\n\tvolume = {20},\n\tnumber = {21},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tyear = {2010},\n\tpages = {22},\n}\n
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\n  \n 2008\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n High Performance Computing and Grids in Action.\n \n \n \n\n\n \n Catlett, C.; Allcock, W. E.; Andrews, P.; Aydt, R.; Bair, R.; Balac, N.; Banister, B.; Barker, T.; Bartelt, M.; Beckman, P.; and others\n\n\n \n\n\n\n In Elsevier, 2008. \n \n\n\n\n
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@inproceedings{catlett_high_2008,\n\ttitle = {High {Performance} {Computing} and {Grids} in {Action}},\n\tbooktitle = {Elsevier},\n\tauthor = {Catlett, Charlie and Allcock, William E. and Andrews, Phil and Aydt, Ruth and Bair, Ray and Balac, Natasha and Banister, Bryan and Barker, Trish and Bartelt, Mark and Beckman, Pete and {others}},\n\tyear = {2008},\n}\n\n
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\n \n\n \n \n \n \n \n Beyond Being There: A Blueprint for Advancing the Design.\n \n \n \n\n\n \n Cummings, J.; Finholt, T.; Foster, I.; Kesselman, C.; and Lawrence, K. A.\n\n\n \n\n\n\n In Development, and Evaluation of Virtual Organizations: Report from an NSF Workshop on Developing VIrtual Organizations, 2008. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{cummings_beyond_2008,\n\ttitle = {Beyond {Being} {There}: {A} {Blueprint} for {Advancing} the {Design}},\n\tbooktitle = {Development, and {Evaluation} of {Virtual} {Organizations}: {Report} from an {NSF} {Workshop} on {Developing} {VIrtual} {Organizations}},\n\tauthor = {Cummings, J. and Finholt, T. and Foster, I. and Kesselman, C. and Lawrence, K. A.},\n\tyear = {2008},\n}\n\n
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\n  \n 2007\n \n \n (3)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n SCEC Cybershake Workflows—automating Probabilistic Seismic Hazard Analysis Calculations.\n \n \n \n\n\n \n Maechling, P.; Deelman, E.; Zhao, L.; Graves, R.; Mehta, G.; Gupta, N.; Mehringer, J.; Kesselman, C.; Callaghan, S.; Okaya, D.; and others\n\n\n \n\n\n\n In Workflows for e-Science, pages 143–163. Springer London, 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@incollection{maechling_scec_2007,\n\ttitle = {{SCEC} {Cybershake} {Workflows}—automating {Probabilistic} {Seismic} {Hazard} {Analysis} {Calculations}},\n\tbooktitle = {Workflows for e-{Science}},\n\tpublisher = {Springer London},\n\tauthor = {Maechling, Philip and Deelman, Ewa and Zhao, Li and Graves, Robert and Mehta, Gaurang and Gupta, Nitin and Mehringer, John and Kesselman, Carl and Callaghan, Scott and Okaya, David and {others}},\n\tyear = {2007},\n\tpages = {143--163},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n Pegasus: Providing Computation Management for Earth Science Applications.\n \n \n \n\n\n \n Deelman, E.; Callaghan, S.; Graves, R.; Jordan, T. H.; Juve, G.; Kesselman, C.; Maechling, P.; Mehta, G.; Meyers, D.; Okaya, D.; and others\n\n\n \n\n\n\n In AGU Fall Meeting Abstracts, volume 1, pages 0463, 2007. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{deelman_pegasus:_2007,\n\ttitle = {Pegasus: {Providing} {Computation} {Management} for {Earth} {Science} {Applications}},\n\tvolume = {1},\n\tbooktitle = {{AGU} {Fall} {Meeting} {Abstracts}},\n\tauthor = {Deelman, E. and Callaghan, S. and Graves, R. and Jordan, T. H. and Juve, G. and Kesselman, C. and Maechling, P. and Mehta, G. and Meyers, D. and Okaya, D. and {others}},\n\tyear = {2007},\n\tpages = {0463},\n}\n\n
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\n \n\n \n \n \n \n \n Globus Medicus: Protected Health Information in Medical Imaging Grids.\n \n \n \n\n\n \n Erberich, S. G.; Silverstein, J. C.; Chervenak, A.; Schuler, R.; Nelson, M. D.; and Kesselman, C.\n\n\n \n\n\n\n , 2: S297–S299. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{erberich_globus_2007,\n\ttitle = {Globus {Medicus}: {Protected} {Health} {Information} in {Medical} {Imaging} {Grids}},\n\tvolume = {2},\n\tauthor = {Erberich, S. G. and Silverstein, J. C. and Chervenak, A. and Schuler, R. and Nelson, M. D. and Kesselman, C.},\n\tyear = {2007},\n\tpages = {S297--S299},\n}\n\n
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\n  \n 2006\n \n \n (2)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Using SCEC Computational Platforms to Advance Seismic Hazard Research.\n \n \n \n\n\n \n Maechling, P. J.; Jordan, T. H.; Minster, J. B.; Moore, R.; and Kesselman, C.\n\n\n \n\n\n\n In AGU Fall Meeting Abstracts, volume 1, pages 0822, 2006. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{maechling_using_2006,\n\ttitle = {Using {SCEC} {Computational} {Platforms} to {Advance} {Seismic} {Hazard} {Research}},\n\tvolume = {1},\n\tbooktitle = {{AGU} {Fall} {Meeting} {Abstracts}},\n\tauthor = {Maechling, P. J. and Jordan, T. H. and Minster, J. B. and Moore, R. and Kesselman, C.},\n\tyear = {2006},\n\tpages = {0822},\n}\n\n
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\n \n\n \n \n \n \n \n Security and Policy for Group Collaboration.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n Technical Report University of Southern California, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@techreport{foster_security_2006,\n\ttitle = {Security and {Policy} for {Group} {Collaboration}},\n\tinstitution = {University of Southern California},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tyear = {2006},\n}\n\n
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\n  \n 2005\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Welcome from the General Co-chairs.\n \n \n \n\n\n \n Walker, D. W.; and Kesselman, C.\n\n\n \n\n\n\n In CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005., volume 1, pages iii–iii, 2005. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{walker_welcome_2005,\n\ttitle = {Welcome from the {General} {Co}-chairs},\n\tvolume = {1},\n\tbooktitle = {{CCGrid} 2005. {IEEE} {International} {Symposium} on {Cluster} {Computing} and the {Grid}, 2005.},\n\tpublisher = {IEEE},\n\tauthor = {Walker, David W. and Kesselman, Carl},\n\tyear = {2005},\n\tpages = {iii--iii},\n}\n\n
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\n  \n 2004\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n Artificial intelligence and grids: workflow planning and beyond.\n \n \n \n \n\n\n \n Gil, Y.; Deelman, E.; Blythe, J.; Kesselman, C.; and Tangmunarunkit, H.\n\n\n \n\n\n\n IEEE Intelligent Systems, 19(1): 26–33. January 2004.\n \n\n\n\n
\n\n\n\n \n \n \"ArtificialPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{gil_artificial_2004,\n\ttitle = {Artificial intelligence and grids: workflow planning and beyond},\n\tvolume = {19},\n\tissn = {1541-1672},\n\tshorttitle = {Artificial intelligence and grids},\n\turl = {http://ieeexplore.ieee.org/document/1265882/},\n\tdoi = {10.1109/MIS.2004.1265882},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-02-12},\n\tjournal = {IEEE Intelligent Systems},\n\tauthor = {Gil, Y. and Deelman, E. and Blythe, J. and Kesselman, C. and Tangmunarunkit, H.},\n\tmonth = jan,\n\tyear = {2004},\n\tpages = {26--33},\n}\n\n
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\n\n\n\n
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\n \n\n \n \n \n \n \n Service Virtualization: Infrastructure and Applications.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n In The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Fransisco, 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@incollection{foster_service_2004,\n\ttitle = {Service {Virtualization}: {Infrastructure} and {Applications}},\n\tbooktitle = {The {Grid} 2: {Blueprint} for a {New} {Computing} {Infrastructure}},\n\tpublisher = {Morgan Kaufmann, San Fransisco},\n\tauthor = {Foster, I. and Kesselman, C.},\n\tyear = {2004},\n}\n\n
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\n\n\n\n
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\n \n\n \n \n \n \n \n The Montage Architecture for Grid-enabled Science Processing of Large, Distributed Datasets.\n \n \n \n\n\n \n Jacob, J. C.; Katz, D. S.; Prince, T.; Berriman, G. B.; Good, J. C.; Laity, A. C.; Deelman, E.; Singh, G.; and Su, M.\n\n\n \n\n\n\n Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@book{jacob_montage_2004,\n\ttitle = {The {Montage} {Architecture} for {Grid}-enabled {Science} {Processing} of {Large}, {Distributed} {Datasets}},\n\tpublisher = {Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration},\n\tauthor = {Jacob, Joseph C. and Katz, Daniel S. and Prince, Thomas and Berriman, G. Bruce and Good, John C. and Laity, Anastasia C. and Deelman, Ewa and Singh, Gurmeet and Su, Mei-Hui},\n\tyear = {2004},\n}\n\n
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\n\n\n\n
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\n \n\n \n \n \n \n \n Mapping Scientific Workflows onto the Grid.\n \n \n \n\n\n \n Deelman, E.; Blythe, J.; Gil, Y.; Kesselman, C.; Mehta, G.; Patil, S.; Su, M.; Vahi, K.; and Livny, M.\n\n\n \n\n\n\n In Across Grids Conference, Nicosia, Cyprus, 2004. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{deelman_mapping_2004,\n\ttitle = {Mapping {Scientific} {Workflows} onto the {Grid}},\n\tbooktitle = {Across {Grids} {Conference}, {Nicosia}, {Cyprus}},\n\tauthor = {Deelman, Ewa and Blythe, J. and Gil, Y. and Kesselman, C. and Mehta, G. and Patil, S. and Su, M. and Vahi, K. and Livny, M.},\n\tyear = {2004},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Pegasus: Mapping Scientific Workflows onto the Grid.\n \n \n \n\n\n \n Deelman, E.; Blythe, J.; Gil, Y.; Kesselman, C.; Mehta, G.; Patil, S.; Su, M.; Vahi, K.; and Livny, M.\n\n\n \n\n\n\n In European Across Grids Conference, pages 11–20, 2004. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{deelman_pegasus:_2004,\n\ttitle = {Pegasus: {Mapping} {Scientific} {Workflows} onto the {Grid}},\n\tbooktitle = {European {Across} {Grids} {Conference}},\n\tauthor = {Deelman, Ewa and Blythe, James and Gil, Yolanda and Kesselman, Carl and Mehta, Gaurang and Patil, Sonal and Su, Mei-Hui and Vahi, Karan and Livny, Miron},\n\tyear = {2004},\n\tpages = {11--20},\n}\n\n
\n
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\n \n\n \n \n \n \n \n The SCEC Community Modeling Environment (scec/cme)-an Overview of Its Architecture and Current Capabilities.\n \n \n \n\n\n \n Maechling, P. J.; Jordan, T. H.; Minster, B.; Moore, R.; Kesselman, C.; Collaboration, S. C. E. C. I. T. R.; and others\n\n\n \n\n\n\n In AGU Fall Meeting Abstracts, volume 1, pages 0754, 2004. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{maechling_scec_2004,\n\ttitle = {The {SCEC} {Community} {Modeling} {Environment} (scec/cme)-an {Overview} of {Its} {Architecture} and {Current} {Capabilities}},\n\tvolume = {1},\n\tbooktitle = {{AGU} {Fall} {Meeting} {Abstracts}},\n\tauthor = {Maechling, Philip J. and Jordan, Thomas H. and Minster, Bernard and Moore, Reagan and Kesselman, Carl and Collaboration, S. C. E. C. I. T. R. and {others}},\n\tyear = {2004},\n\tpages = {0754},\n}\n\n
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\n  \n 2003\n \n \n (6)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Ontology-Based Resource Matching in the Grid – The Grid Meets the Semantic Web.\n \n \n \n \n\n\n \n Tangmunarunkit, H.; Decker, S.; and Kesselman, C.\n\n\n \n\n\n\n In Goos, G.; Hartmanis, J.; van Leeuwen, J.; Fensel, D.; Sycara, K.; and Mylopoulos, J., editor(s), The Semantic Web - ISWC 2003, volume 2870, pages 706–721. Springer Berlin Heidelberg, Berlin, Heidelberg, 2003.\n Series Title: Lecture Notes in Computer Science\n\n\n\n
\n\n\n\n \n \n \"Ontology-BasedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@incollection{goos_ontology-based_2003,\n\taddress = {Berlin, Heidelberg},\n\ttitle = {Ontology-{Based} {Resource} {Matching} in the {Grid} – {The} {Grid} {Meets} the {Semantic} {Web}},\n\tvolume = {2870},\n\tisbn = {978-3-540-20362-9 978-3-540-39718-2},\n\turl = {http://link.springer.com/10.1007/978-3-540-39718-2_45},\n\turldate = {2022-02-12},\n\tbooktitle = {The {Semantic} {Web} - {ISWC} 2003},\n\tpublisher = {Springer Berlin Heidelberg},\n\tauthor = {Tangmunarunkit, Hongsuda and Decker, Stefan and Kesselman, Carl},\n\teditor = {Goos, Gerhard and Hartmanis, Juris and van Leeuwen, Jan and Fensel, Dieter and Sycara, Katia and Mylopoulos, John},\n\tyear = {2003},\n\tdoi = {10.1007/978-3-540-39718-2_45},\n\tnote = {Series Title: Lecture Notes in Computer Science},\n\tpages = {706--721},\n}\n\n
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\n\n\n\n
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\n \n\n \n \n \n \n \n Security for Grid Services.\n \n \n \n\n\n \n Foster, I.; Kesselman, C.; Tsudik, G.; and Tuecke, S.\n\n\n \n\n\n\n In Twelfth Int. Symp. on High Performance Distributed Computing (HPDC-12), pages 22–24, 2003. Seattle, Washington\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{foster_security_2003,\n\ttitle = {Security for {Grid} {Services}},\n\tbooktitle = {Twelfth {Int}. {Symp}. on {High} {Performance} {Distributed} {Computing} ({HPDC}-12)},\n\tpublisher = {Seattle, Washington},\n\tauthor = {Foster, I. and Kesselman, C. and Tsudik, G. and Tuecke, S.},\n\tyear = {2003},\n\tpages = {22--24},\n}\n\n
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\n \n\n \n \n \n \n \n The Physiology of the Grid.\n \n \n \n\n\n \n Foster, I.; Kesselman, C.; Nick, J. M.; and Tuecke, S.\n\n\n \n\n\n\n In Grid computing: Making the global Infrastructure a reality, pages 217–249. John Wiley & Sons, 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@incollection{foster_physiology_2003,\n\ttitle = {The {Physiology} of the {Grid}},\n\tbooktitle = {Grid computing: {Making} the global {Infrastructure} a reality},\n\tpublisher = {John Wiley \\& Sons},\n\tauthor = {Foster, Ian and Kesselman, Carl and Nick, Jeffrey M. and Tuecke, Steven},\n\tyear = {2003},\n\tpages = {217--249},\n}\n\n
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\n \n\n \n \n \n \n \n Internet X. 509 Public Key Infrastructure Proxy Certificate Profile.\n \n \n \n\n\n \n Tuecke, S.; Engert, D.; Foster, I.; Thompson, M.; Pearlman, L.; and Kesselman, C.\n\n\n \n\n\n\n . 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{tuecke_internet_2003,\n\ttitle = {Internet {X}. 509 {Public} {Key} {Infrastructure} {Proxy} {Certificate} {Profile}},\n\tauthor = {Tuecke, S. and Engert, D. and Foster, I. and Thompson, M. and Pearlman, L. and Kesselman, C.},\n\tyear = {2003},\n}\n\n
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\n \n\n \n \n \n \n \n Directed Reading in Web Services.\n \n \n \n\n\n \n Foster, I.; Kesselman, C.; Nick, J. M.; Tuecke, S.; and others\n\n\n \n\n\n\n , 7(5). 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{foster_directed_2003,\n\ttitle = {Directed {Reading} in {Web} {Services}},\n\tvolume = {7},\n\tnumber = {5},\n\tauthor = {Foster, I. and Kesselman, C. and Nick, J. M. and Tuecke, S. and {others}},\n\tyear = {2003},\n}\n\n
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\n \n\n \n \n \n \n \n A Geoscience Grid: The Scec Community Modeling Environment (scec/cme).\n \n \n \n\n\n \n Kesselman, C.; Tangmunarunkit, H.; Gil, Y.; Thiebaux, M.; Decker, S.; Jordan, T. H.; and Maechling, P.\n\n\n \n\n\n\n In AGU Fall Meeting Abstracts, volume 1, pages 0180, 2003. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{kesselman_geoscience_2003,\n\ttitle = {A {Geoscience} {Grid}: {The} {Scec} {Community} {Modeling} {Environment} (scec/cme)},\n\tvolume = {1},\n\tbooktitle = {{AGU} {Fall} {Meeting} {Abstracts}},\n\tauthor = {Kesselman, C. and Tangmunarunkit, H. and Gil, Y. and Thiebaux, M. and Decker, S. and Jordan, T. H. and Maechling, P.},\n\tyear = {2003},\n\tpages = {0180},\n}\n\n
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\n  \n 2002\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Open Grid Services Architecture: A Unifying Framework for Distributed System Integration.\n \n \n \n\n\n \n Foster, I.; Kesselman, C.; Nick, J.; and Tuecke, S.\n\n\n \n\n\n\n Technical Report Technical Report, Globus Project, 2002. URL:[www. globus. org/research/papers/-ogsa. pdf, 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@techreport{foster_open_2002,\n\ttitle = {Open {Grid} {Services} {Architecture}: {A} {Unifying} {Framework} for {Distributed} {System} {Integration}},\n\tinstitution = {Technical Report, Globus Project, 2002. URL:[www. globus. org/research/papers/-ogsa. pdf},\n\tauthor = {Foster, I. and Kesselman, C. and Nick, J. and Tuecke, S.},\n\tyear = {2002},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n An Open Grid Services Architecture for Distributed Systems Integration.\n \n \n \n\n\n \n Foster, I.; Kesselman, C.; Nick, J. M.; and Tuecke, S.\n\n\n \n\n\n\n In Proceedings of ICPP, 2002. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{foster_open_2002-1,\n\ttitle = {An {Open} {Grid} {Services} {Architecture} for {Distributed} {Systems} {Integration}},\n\tbooktitle = {Proceedings of {ICPP}},\n\tauthor = {Foster, Ian and Kesselman, Carl and Nick, Jeffrey M. and Tuecke, Steven},\n\tyear = {2002},\n}\n\n
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\n \n\n \n \n \n \n \n A Community Authorization Service for Group Collaboration.\n \n \n \n\n\n \n Pearlman, L.; Welch, V.; Foster, I.; Kesselman, C.; Tuecke, S.; and others\n\n\n \n\n\n\n In IEEE 3\\textsuperscriptrd International Workshop on Policies for Distributed Systems and Networks, 2002. Jun\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{pearlman_community_2002,\n\ttitle = {A {Community} {Authorization} {Service} for {Group} {Collaboration}},\n\tbooktitle = {{IEEE} 3{\\textbackslash}textsuperscriptrd {International} {Workshop} on {Policies} for {Distributed} {Systems} and {Networks}},\n\tpublisher = {Jun},\n\tauthor = {Pearlman, Laura and Welch, Von and Foster, Ian and Kesselman, Carl and Tuecke, Steven and {others}},\n\tyear = {2002},\n}\n\n
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\n \n\n \n \n \n \n \n The Earth System Grid Ii: Turning Climate Datasets into Community Resources.\n \n \n \n\n\n \n Foster, I.; Alpert, E.; Chervenak, A.; Drach, B.; Kesselman, C.; Nefedova, V.; Middleton, D.; Shoshani, A.; Sim, A.; and Williams, D.\n\n\n \n\n\n\n In Annual Meeting of the American Meteorological Society, 2002. \n \n\n\n\n
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\n 
@inproceedings{foster_earth_2002,\n\ttitle = {The {Earth} {System} {Grid} {Ii}: {Turning} {Climate} {Datasets} into {Community} {Resources}},\n\tbooktitle = {Annual {Meeting} of the {American} {Meteorological} {Society}},\n\tauthor = {Foster, Ian and Alpert, Ethan and Chervenak, Ann and Drach, Bob and Kesselman, Carl and Nefedova, Veronika and Middleton, Don and Shoshani, Arie and Sim, Alex and Williams, Dean},\n\tyear = {2002},\n}\n\n
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\n  \n 2001\n \n \n (5)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n High Performance Remote Access to Climate Simulation Data.\n \n \n \n\n\n \n Allcock, B.; Foster, I.; Nefedova, V.; Chervenak, A.; Deelman, E.; Kesselman, C.; Lee, J.; Sim, A.; Shoshani, A.; Drach, B.; and others\n\n\n \n\n\n\n In Proc. SC2001, 2001. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{allcock_high_2001,\n\ttitle = {High {Performance} {Remote} {Access} to {Climate} {Simulation} {Data}},\n\tbooktitle = {Proc. {SC2001}},\n\tauthor = {Allcock, B. and Foster, I. and Nefedova, V. and Chervenak, A. and Deelman, E. and Kesselman, C. and Lee, J. and Sim, A. and Shoshani, A. and Drach, B. and {others}},\n\tyear = {2001},\n}\n\n
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\n \n\n \n \n \n \n \n Representing Virtual Data: A Catalog Architecture for Location and Materialization Transparency.\n \n \n \n\n\n \n Deelman, E.; Foster, I.; Kesselman, C.; and Livny, M.\n\n\n \n\n\n\n Technical Report Technical Report GriPhyN-2001-14, 2001.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@techreport{deelman_representing_2001,\n\ttitle = {Representing {Virtual} {Data}: {A} {Catalog} {Architecture} for {Location} and {Materialization} {Transparency}},\n\tinstitution = {Technical Report GriPhyN-2001-14},\n\tauthor = {Deelman, E. and Foster, I. and Kesselman, C. and Livny, M.},\n\tyear = {2001},\n}\n\n
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\n \n\n \n \n \n \n \n The Grid Notification Framework.\n \n \n \n\n\n \n Gullapalli, S.; Czajkowski, K.; Kesselman, C.; and Fitzgerald, S.\n\n\n \n\n\n\n In Global Grid Forum, Junho de, 2001. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{gullapalli_grid_2001,\n\ttitle = {The {Grid} {Notification} {Framework}},\n\tbooktitle = {Global {Grid} {Forum}, {Junho} de},\n\tauthor = {Gullapalli, S. and Czajkowski, K. and Kesselman, C. and Fitzgerald, S.},\n\tyear = {2001},\n}\n\n
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\n \n\n \n \n \n \n \n NEESGgrid: A Distributed Virtual Laboratory for Advanced Earthquake Experimentation and Simulation.\n \n \n \n\n\n \n Prudhomme, T.; Kesselman, C.; Finholt, T.; Foster, I.; Parsons, D.; Abrams, D.; Bardet, J. P.; Pennington, R.; Towns, J.; Butler, R.; and others\n\n\n \n\n\n\n Technical Report Technical Report 2001-01, Scoping Study, NEESgrid, 2001.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@techreport{prudhomme_neesggrid:_2001,\n\ttitle = {{NEESGgrid}: {A} {Distributed} {Virtual} {Laboratory} for {Advanced} {Earthquake} {Experimentation} and {Simulation}},\n\tinstitution = {Technical Report 2001-01, Scoping Study, NEESgrid},\n\tauthor = {Prudhomme, Tom and Kesselman, Carl and Finholt, Tom and Foster, Ian and Parsons, Dennis and Abrams, Dan and Bardet, J. P. and Pennington, Rob and Towns, John and Butler, Randy and {others}},\n\tyear = {2001},\n}\n\n
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\n \n\n \n \n \n \n \n The Grads Project: Software Support for High Performance Grid Applications-int.\n \n \n \n\n\n \n Berman, F.; Chien, T.; Cooper, K.; Dongarra, J.; Foster, I.; Gannon, D.; Johnson, L.; Kennedy, K.; Kasselman, C.; Mellor-Crummey, J.; and others\n\n\n \n\n\n\n , 15: 327–344. 2001.\n \n\n\n\n
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\n 
@article{berman_grads_2001,\n\ttitle = {The {Grads} {Project}: {Software} {Support} for {High} {Performance} {Grid} {Applications}-int},\n\tvolume = {15},\n\tauthor = {Berman, F. and Chien, To and Cooper, K. and Dongarra, J. and Foster, I. and Gannon, D. and Johnson, L. and Kennedy, K. and Kasselman, C. and Mellor-Crummey, J. and {others}},\n\tyear = {2001},\n\tpages = {327--344},\n}\n\n
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\n  \n 2000\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Computational Grids.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n In International Conference on Vector and Parallel Processing: Selected Papers and Invited Talks, of Lecture Notes in Computer Science, pages 3, 2000. Elsevier\n \n\n\n\n
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@inproceedings{foster_computational_2000,\n\tseries = {Lecture {Notes} in {Computer} {Science}},\n\ttitle = {Computational {Grids}},\n\tbooktitle = {International {Conference} on {Vector} and {Parallel} {Processing}: {Selected} {Papers} and {Invited} {Talks}},\n\tpublisher = {Elsevier},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tyear = {2000},\n\tpages = {3},\n}\n\n
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\n \n\n \n \n \n \n \n The Grid: Where We've Been, Where We Are, and Where We're Going.\n \n \n \n\n\n \n Kesselmann, C.\n\n\n \n\n\n\n In euromicro-pdp, 2000. IEEE\n \n\n\n\n
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@inproceedings{kesselmann_grid:_2000,\n\ttitle = {The {Grid}: {Where} {We}'ve {Been}, {Where} {We} {Are}, and {Where} {We}'re {Going}},\n\tbooktitle = {euromicro-pdp},\n\tpublisher = {IEEE},\n\tauthor = {Kesselmann, C.},\n\tyear = {2000},\n}\n\n
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\n \n\n \n \n \n \n \n Panel on Metacomputing.\n \n \n \n\n\n \n Getov, V.; Kacsuk, P.; Kesselman, C.; Kloeckner, K.; Laforenza, D.; and Vajda, F.\n\n\n \n\n\n\n In Proceedings of the 8\\textsuperscriptth Euromicro conference on Parallel and distributed processing, pages 254–254, 2000. IEEE Computer Society\n \n\n\n\n
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@inproceedings{getov_panel_2000,\n\ttitle = {Panel on {Metacomputing}},\n\tbooktitle = {Proceedings of the 8{\\textbackslash}textsuperscriptth {Euromicro} conference on {Parallel} and distributed processing},\n\tpublisher = {IEEE Computer Society},\n\tauthor = {Getov, Vladimir and Kacsuk, Peter and Kesselman, Carl and Kloeckner, Konrad and Laforenza, Domenico and Vajda, Ferenc},\n\tyear = {2000},\n\tpages = {254--254},\n}\n\n
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\n  \n 1999\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n The Globus Toolkit.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n In The Grid: Blueprint for a new computing infrastructure, pages 259–278. Morgan Kaufman, 1999.\n \n\n\n\n
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@incollection{foster_globus_1999,\n\ttitle = {The {Globus} {Toolkit}},\n\tbooktitle = {The {Grid}: {Blueprint} for a new computing infrastructure},\n\tpublisher = {Morgan Kaufman},\n\tauthor = {Foster, Ian and Kesselman, Carl},\n\tyear = {1999},\n\tpages = {259--278},\n}\n\n
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\n \n\n \n \n \n \n \n Security, Accounting, and Assurance.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n ,395–420. 1999.\n \n\n\n\n
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@article{foster_security_1999,\n\ttitle = {Security, {Accounting}, and {Assurance}},\n\tauthor = {Foster, I. and Kesselman, C.},\n\tyear = {1999},\n\tpages = {395--420},\n}\n\n
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\n \n\n \n \n \n \n \n Computational Grids.\n \n \n \n\n\n \n Kesselman, C.; and Foster, I.\n\n\n \n\n\n\n In In The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufman, 1999.\n \n\n\n\n
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@incollection{kesselman_computational_1999,\n\ttitle = {Computational {Grids}},\n\tbooktitle = {In {The} {Grid}: {Blueprint} for a {New} {Computing} {Infrastructure}},\n\tpublisher = {Morgan Kaufman},\n\tauthor = {Kesselman, C. and Foster, I.},\n\tyear = {1999},\n}\n\n
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\n \n\n \n \n \n \n \n The Grid: Blueprint for a Future Computing Infrastructure.\n \n \n \n\n\n \n Kesselman, C.; and Foster, I.\n\n\n \n\n\n\n . 1999.\n \n\n\n\n
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@article{kesselman_grid:_1999,\n\ttitle = {The {Grid}: {Blueprint} for a {Future} {Computing} {Infrastructure}},\n\tauthor = {Kesselman, C. and Foster, I.},\n\tyear = {1999},\n}\n\n
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\n \n\n \n \n \n \n \n Prototyping an Earth System Grid.\n \n \n \n\n\n \n Feng, W.; Foster, I.; Hammond, S.; Hibbard, B.; Kesselman, C.; Shoshani, A.; Tierney, B.; and Williams, D.\n\n\n \n\n\n\n July, 1999.\n \n\n\n\n
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@book{feng_prototyping_1999,\n\ttitle = {Prototyping an {Earth} {System} {Grid}},\n\tpublisher = {July},\n\tauthor = {Feng, W. and Foster, I. and Hammond, S. and Hibbard, B. and Kesselman, C. and Shoshani, A. and Tierney, B. and Williams, D.},\n\tyear = {1999},\n}\n\n
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\n  \n 1998\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Computational Grids: The Future of High Performance Distributed Computing.\n \n \n \n\n\n \n Foster, I.; and Kesselman, C.\n\n\n \n\n\n\n Morgan Kaufmann Publishers, 1998.\n \n\n\n\n
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@book{foster_computational_1998,\n\ttitle = {Computational {Grids}: {The} {Future} of {High} {Performance} {Distributed} {Computing}},\n\tpublisher = {Morgan Kaufmann Publishers},\n\tauthor = {Foster, I. and Kesselman, C.},\n\tyear = {1998},\n}\n\n
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\n  \n 1997\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Globus: A Metacomputing Infrastructure Toolkit.\n \n \n \n\n\n \n Globus, I. F.; and Kesselman, C.\n\n\n \n\n\n\n , 11(2): 115–128. 1997.\n \n\n\n\n
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@article{globus_globus:_1997,\n\ttitle = {Globus: {A} {Metacomputing} {Infrastructure} {Toolkit}.},\n\tvolume = {11},\n\tnumber = {2},\n\tauthor = {Globus, I. Foster and Kesselman, C.},\n\tyear = {1997},\n\tpages = {115--128},\n}\n\n
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