Mining Semantic Relations in Data References to Understand the Roles of Research Data in Academic Literature
dc.contributor.author | Fan, Lizhou | |
dc.contributor.author | Lafia, Sara | |
dc.contributor.author | Wofford, Morgan | |
dc.contributor.author | Thomer, Andrea | |
dc.contributor.author | Yakel, Elizabeth | |
dc.contributor.author | Hemphill, Libby | |
dc.date.accessioned | 2023-09-01T19:46:57Z | |
dc.date.available | 2023-09-01T19:46:57Z | |
dc.date.issued | 2023-09-01 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/177535 | en |
dc.description.abstract | Research data serves important roles in scientific discovery and academic innovation. To appropriately assign credit for data work and to measure the value of research data, it is essential to articulate how data are actually used in research. We leveraged a combination of computational methods and human analysis to characterize different types of data use by mining semantic relations from the phrases where data are referenced in academic literature. In particular, we investigated references to data in the bibliography of a large social science data archive, the Inter-university Consortium for Political and Social Research (ICPSR). After retrieving and extracting semantic relations as subject-relation-object triples, we used rule-based methods to classify them. We then annotated samples from 11 frequent classes of data reference triples and found that they vary primarily along two dimensions of data use: proximity and function. Proximity describes the distance between the author and the data they reference (e.g., direct or indirect engagement). Function describes the role that data plays in each reference (e.g., describing interaction or providing context). These semantic relationships between authors and data reveal the ways data are used in scientific publications. Evidence of the variety of ways data are used can help stakeholders in research data curation and stewardship – including data providers, data curators, and data users – recognize the myriad ways that their investments in data sharing are realized. | en_US |
dc.description.sponsorship | National Science Foundation, grant no. 1930645 | en_US |
dc.description.sponsorship | National Science Foundation, grant no. 2121789 | en_US |
dc.language.iso | en_US | en_US |
dc.subject | information extraction | en_US |
dc.subject | knowledge discovery | en_US |
dc.subject | research data management | en_US |
dc.subject | semantic triples | en_US |
dc.subject | text mining | en_US |
dc.title | Mining Semantic Relations in Data References to Understand the Roles of Research Data in Academic Literature | en_US |
dc.type | Conference Paper | en_US |
dc.subject.hlbsecondlevel | Information Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | Inter-university Consortium for Political and Social Research | en_US |
dc.contributor.affiliationother | School of Information, University of Arizona | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/177535/1/JCDL_Mining_Semantic_Relations_in_Data_References.pdf | |
dc.identifier.doi | https://dx.doi.org/10.7302/8089 | |
dc.identifier.source | Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL) | en_US |
dc.identifier.orcid | 0000-0002-7962-9113 | en_US |
dc.identifier.orcid | 0000-0002-5896-7295 | en_US |
dc.identifier.orcid | 0000-0002-4688-0133 | en_US |
dc.identifier.orcid | 0000-0001-6238-3498 | en_US |
dc.identifier.orcid | 0000-0002-8792-6900 | en_US |
dc.identifier.orcid | 0000-0002-3793-7281 | en_US |
dc.description.filedescription | Description of JCDL_Mining_Semantic_Relations_in_Data_References.pdf : Main article | |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Fan, Lizhou; 0000-0002-7962-9113 | en_US |
dc.identifier.name-orcid | Lafia, Sara; 0000-0002-5896-7295 | en_US |
dc.identifier.name-orcid | Wofford, Morgan; 0000-0002-4688-0133 | en_US |
dc.identifier.name-orcid | Thomer, Andrea; 0000-0001-6238-3498 | en_US |
dc.identifier.name-orcid | Yakel, Elizabeth; 0000-0002-8792-6900 | en_US |
dc.identifier.name-orcid | Hemphill, Libby; 0000-0002-3793-7281 | en_US |
dc.working.doi | 10.7302/8089 | en_US |
dc.owningcollname | Information, School of (SI) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.