@article{manghi_challenges_2024,
	title = {Challenges in building {Scholarly} {Knowledge} {Graphs} for research assessment in {Open} {Science}},
	issn = {2641-3337},
	url = {https://doi.org/10.1162/qss_a_00322},
	doi = {10.1162/qss_a_00322},
	abstract = {Open Science has revolutionized scholarly communication and research assessment by introducing research data and software as first-class citizens. Scholarly Knowledge Graphs (SKGs) are expected to play a crucial role in generating research assessment indicators being able to aggregate bibliographic metadata records and semantic relationships describing all research products and their links (e.g., citations, affiliations, funding). However, the rapid advancement of Open Science has led to publication workflows that do not adequately support and guarantee the authenticity of products and metadata quality required for research assessment. Additionally, the heterogeneity of research communities and the multitude of data sources and exchange formats complicate the provision of consistent and stable SKGs. This work builds upon the experience gained from pioneering and addressing these challenges in the OpenAIRE Graph SKG. The aim is twofold and broader. Firstly, identifying obstacles to the creation of SKGs for research assessment caused by the state-of-the-art publishing workflows for publications, software, and data. Secondly, repurposing SKGs as tools to monitor such workflows to identify and heal their shortcomings, taking advantage of tools, techniques, and practices that support the actors involved, namely research communities, scientists, organizations, data source providers, and SKG providers, at improving the Open Science scholarly publishing ecosystem.https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss\_a\_00322},
	urldate = {2024-08-12},
	journal = {Quantitative Science Studies},
	author = {Manghi, Paolo},
	month = aug,
	year = {2024},
	pages = {1--31},
}

{"_id":"DZJH6eAN996GGEGds","bibbaseid":"manghi-challengesinbuildingscholarlyknowledgegraphsforresearchassessmentinopenscience-2024","author_short":["Manghi, P."],"bibdata":{"bibtype":"article","type":"article","title":"Challenges in building Scholarly Knowledge Graphs for research assessment in Open Science","issn":"2641-3337","url":"https://doi.org/10.1162/qss_a_00322","doi":"10.1162/qss_a_00322","abstract":"Open Science has revolutionized scholarly communication and research assessment by introducing research data and software as first-class citizens. Scholarly Knowledge Graphs (SKGs) are expected to play a crucial role in generating research assessment indicators being able to aggregate bibliographic metadata records and semantic relationships describing all research products and their links (e.g., citations, affiliations, funding). However, the rapid advancement of Open Science has led to publication workflows that do not adequately support and guarantee the authenticity of products and metadata quality required for research assessment. Additionally, the heterogeneity of research communities and the multitude of data sources and exchange formats complicate the provision of consistent and stable SKGs. This work builds upon the experience gained from pioneering and addressing these challenges in the OpenAIRE Graph SKG. The aim is twofold and broader. Firstly, identifying obstacles to the creation of SKGs for research assessment caused by the state-of-the-art publishing workflows for publications, software, and data. Secondly, repurposing SKGs as tools to monitor such workflows to identify and heal their shortcomings, taking advantage of tools, techniques, and practices that support the actors involved, namely research communities, scientists, organizations, data source providers, and SKG providers, at improving the Open Science scholarly publishing ecosystem.https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00322","urldate":"2024-08-12","journal":"Quantitative Science Studies","author":[{"propositions":[],"lastnames":["Manghi"],"firstnames":["Paolo"],"suffixes":[]}],"month":"August","year":"2024","pages":"1–31","bibtex":"@article{manghi_challenges_2024,\n\ttitle = {Challenges in building {Scholarly} {Knowledge} {Graphs} for research assessment in {Open} {Science}},\n\tissn = {2641-3337},\n\turl = {https://doi.org/10.1162/qss_a_00322},\n\tdoi = {10.1162/qss_a_00322},\n\tabstract = {Open Science has revolutionized scholarly communication and research assessment by introducing research data and software as first-class citizens. Scholarly Knowledge Graphs (SKGs) are expected to play a crucial role in generating research assessment indicators being able to aggregate bibliographic metadata records and semantic relationships describing all research products and their links (e.g., citations, affiliations, funding). However, the rapid advancement of Open Science has led to publication workflows that do not adequately support and guarantee the authenticity of products and metadata quality required for research assessment. Additionally, the heterogeneity of research communities and the multitude of data sources and exchange formats complicate the provision of consistent and stable SKGs. This work builds upon the experience gained from pioneering and addressing these challenges in the OpenAIRE Graph SKG. The aim is twofold and broader. Firstly, identifying obstacles to the creation of SKGs for research assessment caused by the state-of-the-art publishing workflows for publications, software, and data. Secondly, repurposing SKGs as tools to monitor such workflows to identify and heal their shortcomings, taking advantage of tools, techniques, and practices that support the actors involved, namely research communities, scientists, organizations, data source providers, and SKG providers, at improving the Open Science scholarly publishing ecosystem.https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss\\_a\\_00322},\n\turldate = {2024-08-12},\n\tjournal = {Quantitative Science Studies},\n\tauthor = {Manghi, Paolo},\n\tmonth = aug,\n\tyear = {2024},\n\tpages = {1--31},\n}\n\n","author_short":["Manghi, P."],"key":"manghi_challenges_2024","id":"manghi_challenges_2024","bibbaseid":"manghi-challengesinbuildingscholarlyknowledgegraphsforresearchassessmentinopenscience-2024","role":"author","urls":{"Paper":"https://doi.org/10.1162/qss_a_00322"},"metadata":{"authorlinks":{}},"downloads":3},"bibtype":"article","biburl":"https://api.zotero.org/groups/4790165/items?key=qWYUkNg8G2tSrs1m5i7SsKOn&format=bibtex&limit=100","dataSources":["txmtuJDjhqHfaZE3C","wkZmECJAmJTTcjXCL","ttiB3rxTuWH3fiHv3","QHRyMQvCoxGqqkZfo"],"keywords":[],"search_terms":["challenges","building","scholarly","knowledge","graphs","research","assessment","open","science","manghi"],"title":"Challenges in building Scholarly Knowledge Graphs for research assessment in Open Science","year":2024,"downloads":3}