Semi automated process for generating knowledge graphs for marginalized community doctoral-recipients.
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Authors
Keshan, Neha
Fontaine, Kathy
Hendler, James A.
Issue Date
2022-10-13
Type
Preprint
Language
en_US
Keywords
Semiautomation process , Knowledge graphs , Institute demographics , Graduate mobility , NSF doctoral recipients survey data
Alternative Title
Abstract
Purpose – This paper aims to describe the “InDO: Institute Demographic Ontology” and demonstrates the
InDO-based semiautomated process for both generating and extending a knowledge graph to provide a
comprehensive resource for marginalized US graduate students. The knowledge graph currently consists of
instances related to the semistructured National Science Foundation Survey of Earned Doctorates (NSF SED)
2019 analysis report data tables. These tables contain summary statistics of an institute’s doctoral recipients
based on a variety of demographics. Incorporating institute Wikidata links ultimately produces a table of
unique, clearly readable data.
Design/methodology/approach – The authors use a customized semantic extract transform and loader
(SETLr) script to ingest data from 2019 US doctoral-granting institute tables and preprocessed NSF SED
Tables 1, 3, 4 and 9. The generated InDO knowledge graph is evaluated using two methods. First, the authors
compare competency questions’ sparql results from both the semiautomatically and manually generated
graphs. Second, the authors expand the questions to provide a better picture of an institute’s doctoral-recipient
demographics within study fields.
Findings – With some preprocessing and restructuring of the NSF SED highly interlinked tables
into a more parsable format, one can build the required knowledge graph using a semiautomated
process.
Originality/value – The InDO knowledge graph allows the integration of US doctoral-granting institutes
demographic data based on NSF SED data tables and presentation in machine-readable form using a new
semiautomated methodology.
Description
Full Citation
Keshan, N., Fontaine, K. and Hendler, J.A., 2022. Semiautomated process for generating knowledge graphs for marginalized community doctoral-recipients. International Journal of Web Information Systems, (ahead-of-print).
Publisher
Emerald Publishing Limited
Terms of Use
Journal
Volume
Issue
PubMed ID
DOI
ISSN
1744-0084