Near-Real-Time OGC Catalogue Service for Geoscience Big Data. Song, J. & Di, L. ISPRS International Journal of Geo-Information, 6(11):337, 2017. ![Near-Real-Time OGC Catalogue Service for Geoscience Big Data [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Geoscience data are typically big data, and they are distributed in various agencies and individuals worldwide. Efficient data sharing and interoperability are important for managing and applying geoscience data. The OGC (Open Geospatial Consortium) Catalogue Service for the Web (CSW) is an open interoperability standard for supporting the discovery of geospatial data. In the past, regular OGC catalogue services have been studied, but few studies have discussed a near-real-time OGC catalogue service for geoscience big data. A near-real-time OGC catalogue service requires frequent updates of a metadata repository in a short time. When dealing with massive amounts of geoscience data, this comprises an extremely challenging issue. Discovering these data via an OGC catalogue service in near real-time is desirable. In this study, we focus on how the near-real-time OGC catalogue service is realized through several lightweight data structures, algorithms, and tools. We propose a framework of a near-real-time OGC catalogue service and discuss each element of the framework to which more attention should be paid when dealing with the massive amounts of real-time data, followed by a review of several methods that need to be considered in a near-real-time OGC CSW service. A case study on providing an OGC catalogue service to Unidata real-time data is presented to demonstrate how specific methods are utilized to deal with real-time data. The goal of this paper is to fill the gap in knowledge regarding an OGC catalogue service for geoscience big data, and it has realistic significance in facilitating a near-real-time OGC catalogue service.
@article{song_near-real-time_2017,
title = {Near-{Real}-{Time} {OGC} {Catalogue} {Service} for {Geoscience} {Big} {Data}},
volume = {6},
issn = {2220-9964},
url = {http://www.mdpi.com/2220-9964/6/11/337},
doi = {10.3390/ijgi6110337},
abstract = {Geoscience data are typically big data, and they are distributed in various agencies and individuals worldwide. Efficient data sharing and interoperability are important for managing and applying geoscience data. The OGC (Open Geospatial Consortium) Catalogue Service for the Web (CSW) is an open interoperability standard for supporting the discovery of geospatial data. In the past, regular OGC catalogue services have been studied, but few studies have discussed a near-real-time OGC catalogue service for geoscience big data. A near-real-time OGC catalogue service requires frequent updates of a metadata repository in a short time. When dealing with massive amounts of geoscience data, this comprises an extremely challenging issue. Discovering these data via an OGC catalogue service in near real-time is desirable. In this study, we focus on how the near-real-time OGC catalogue service is realized through several lightweight data structures, algorithms, and tools. We propose a framework of a near-real-time OGC catalogue service and discuss each element of the framework to which more attention should be paid when dealing with the massive amounts of real-time data, followed by a review of several methods that need to be considered in a near-real-time OGC CSW service. A case study on providing an OGC catalogue service to Unidata real-time data is presented to demonstrate how specific methods are utilized to deal with real-time data. The goal of this paper is to fill the gap in knowledge regarding an OGC catalogue service for geoscience big data, and it has realistic significance in facilitating a near-real-time OGC catalogue service.},
number = {11},
journal = {ISPRS International Journal of Geo-Information},
author = {Song, Jia and Di, Liping},
year = {2017},
keywords = {big data, catalogue service, csw, metadata, real time, unidata},
pages = {337},
file = {Attachment:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/UGMCN7GY/2017 - Song, Di - Near-Real-Time OGC Catalogue Service for Geoscience Big Data.pdf:application/pdf}
}
Downloads: 0
{"_id":"gr8nubdhoZbnbzvSn","bibbaseid":"song-di-nearrealtimeogccatalogueserviceforgeosciencebigdata-2017","downloads":0,"creationDate":"2019-01-23T19:47:22.490Z","title":"Near-Real-Time OGC Catalogue Service for Geoscience Big Data","author_short":["Song, J.","Di, L."],"year":2017,"bibtype":"article","biburl":"http://crop.csiss.gmu.edu/data/csiss_pub.bib","bibdata":{"bibtype":"article","type":"article","title":"Near-Real-Time OGC Catalogue Service for Geoscience Big Data","volume":"6","issn":"2220-9964","url":"http://www.mdpi.com/2220-9964/6/11/337","doi":"10.3390/ijgi6110337","abstract":"Geoscience data are typically big data, and they are distributed in various agencies and individuals worldwide. Efficient data sharing and interoperability are important for managing and applying geoscience data. The OGC (Open Geospatial Consortium) Catalogue Service for the Web (CSW) is an open interoperability standard for supporting the discovery of geospatial data. In the past, regular OGC catalogue services have been studied, but few studies have discussed a near-real-time OGC catalogue service for geoscience big data. A near-real-time OGC catalogue service requires frequent updates of a metadata repository in a short time. When dealing with massive amounts of geoscience data, this comprises an extremely challenging issue. Discovering these data via an OGC catalogue service in near real-time is desirable. In this study, we focus on how the near-real-time OGC catalogue service is realized through several lightweight data structures, algorithms, and tools. We propose a framework of a near-real-time OGC catalogue service and discuss each element of the framework to which more attention should be paid when dealing with the massive amounts of real-time data, followed by a review of several methods that need to be considered in a near-real-time OGC CSW service. A case study on providing an OGC catalogue service to Unidata real-time data is presented to demonstrate how specific methods are utilized to deal with real-time data. The goal of this paper is to fill the gap in knowledge regarding an OGC catalogue service for geoscience big data, and it has realistic significance in facilitating a near-real-time OGC catalogue service.","number":"11","journal":"ISPRS International Journal of Geo-Information","author":[{"propositions":[],"lastnames":["Song"],"firstnames":["Jia"],"suffixes":[]},{"propositions":[],"lastnames":["Di"],"firstnames":["Liping"],"suffixes":[]}],"year":"2017","keywords":"big data, catalogue service, csw, metadata, real time, unidata","pages":"337","file":"Attachment:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/UGMCN7GY/2017 - Song, Di - Near-Real-Time OGC Catalogue Service for Geoscience Big Data.pdf:application/pdf","bibtex":"@article{song_near-real-time_2017,\n\ttitle = {Near-{Real}-{Time} {OGC} {Catalogue} {Service} for {Geoscience} {Big} {Data}},\n\tvolume = {6},\n\tissn = {2220-9964},\n\turl = {http://www.mdpi.com/2220-9964/6/11/337},\n\tdoi = {10.3390/ijgi6110337},\n\tabstract = {Geoscience data are typically big data, and they are distributed in various agencies and individuals worldwide. Efficient data sharing and interoperability are important for managing and applying geoscience data. The OGC (Open Geospatial Consortium) Catalogue Service for the Web (CSW) is an open interoperability standard for supporting the discovery of geospatial data. In the past, regular OGC catalogue services have been studied, but few studies have discussed a near-real-time OGC catalogue service for geoscience big data. A near-real-time OGC catalogue service requires frequent updates of a metadata repository in a short time. When dealing with massive amounts of geoscience data, this comprises an extremely challenging issue. Discovering these data via an OGC catalogue service in near real-time is desirable. In this study, we focus on how the near-real-time OGC catalogue service is realized through several lightweight data structures, algorithms, and tools. We propose a framework of a near-real-time OGC catalogue service and discuss each element of the framework to which more attention should be paid when dealing with the massive amounts of real-time data, followed by a review of several methods that need to be considered in a near-real-time OGC CSW service. A case study on providing an OGC catalogue service to Unidata real-time data is presented to demonstrate how specific methods are utilized to deal with real-time data. The goal of this paper is to fill the gap in knowledge regarding an OGC catalogue service for geoscience big data, and it has realistic significance in facilitating a near-real-time OGC catalogue service.},\n\tnumber = {11},\n\tjournal = {ISPRS International Journal of Geo-Information},\n\tauthor = {Song, Jia and Di, Liping},\n\tyear = {2017},\n\tkeywords = {big data, catalogue service, csw, metadata, real time, unidata},\n\tpages = {337},\n\tfile = {Attachment:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/UGMCN7GY/2017 - Song, Di - Near-Real-Time OGC Catalogue Service for Geoscience Big Data.pdf:application/pdf}\n}\n\n","author_short":["Song, J.","Di, L."],"key":"song_near-real-time_2017","id":"song_near-real-time_2017","bibbaseid":"song-di-nearrealtimeogccatalogueserviceforgeosciencebigdata-2017","role":"author","urls":{"Paper":"http://www.mdpi.com/2220-9964/6/11/337"},"keyword":["big data","catalogue service","csw","metadata","real time","unidata"],"downloads":0,"html":"","metadata":{"authorlinks":{}}},"search_terms":["near","real","time","ogc","catalogue","service","geoscience","big","data","song","di"],"keywords":["big data","catalogue service","csw","metadata","real time","unidata"],"authorIDs":["5bd89df764f10d10000003e1"],"dataSources":["DTsmNeo3d3wppoQWa"]}