Ontologies supporting research related information foraging using knowledge graphs - literature survey and holistic model mapping
1. Viet Bach Nguyen, University of Economics, Prague, CZE
Gollam Rabby, University of Economics, Prague, CZE
Vojtěch Svátek, University of Economics, Prague, CZE
Oscar Corcho, Universidad Politécnica de Madrid, ESP
Ontologies Supporting Research-related
Information Foraging Using Knowledge
Graphs: Literature Survey and Holistic
Model Mapping
EKAW 2020 - 22nd International Conference on Knowledge
Engineering and Knowledge Management
Project KNERD - Knowledge Engineering for Researcher Data
18.09.2020
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Content
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- Motivations
- Related work
- Methodology
- Literature survey for ontologies
- Competency questions & holistic model
- Ontology-model coverage
- Conclusions
Project repository with results and resources:
https://github.com/nvbach91/iga-knerd
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1 - Motivations
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- Information need of researchers is based on the their roles
- Academic domain comprises many generic concepts and
relationships on which information is sought and makes it
possible to elevate to structured databases on the web
- Usage of knowledge graphs (KGs) improves dynamicity and
integration compared to traditional databases
- Scarcity of KGs and datasets for the academic domain
- Reuse of existing ontologies and their combinations helps
better create KGs
- Identifying missing and overlapping features across ontologies
describing parts of the same domain improves the quality of
such KG
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2 - Related work
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- Ruiz-Iniesta, A., Corcho, O.: A Review of Ontologies for Describing Scholarly
and Scientific Documents
- Focuses on research publications
- Brack, A., Hoppe, A., Stocker, M., Auer, S., Ewerth, R.: Requirements Analysis
for an Open Research Knowledge Graph
- Focuses on literature-oriented tasks of scientists
- Pertsas, V., Constantopoulos, P.: Scholarly Ontology: Modeling Scholarly
Practices
- Focuses on experiments and paper writing
Research gap: survey of ontology covering the concepts referenced by daily
activities of researchers in different roles
Our contribution: updating scholarly research ontology surveys and aligning
ontologies with an analysis of information needs of different roles of
researchers.
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3 - Methodology - how we did it
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- Literature survey to update the previous scholarly/research
surveys on ontologies
- Creating a holistic conceptual graph model using a
competency question analysis that yields specific information
needs based on the roles of researchers
- Aligning entities and relationships in the ontologies with the
holistic model to identify missing features and overlaps
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4 - Literature survey
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- Finding ontologies, projects & papers on Scopus, Web of
Science, Google Scholar & Google, Linked Open
Vocabularies using keywords and filters
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4 - Literature survey results
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- Table of metadata related to relevant ontologies
- 43 ontologies in total, old and new
- 34 well-documented ontologies chosen for further analysis
SO, OLOUD, VIVO, CCSO, AIISO, FRAPO, ORKG, ESO/EAO, SEDE,
OAD, AcademIS, CSO, BIBO, FOAF-Academic, SemSur, RO, SWRC,
ABET, RPO, CERIF, FaBiO, CiTO, BiRO, C4O, DoCO, PSO, PRO, PWO,
SCoRO, DataCite, BiDO, FiveStars, FR, OCO
https://github.com/nvbach91/iga-knerd/tree/master/ontologies
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5 - Competency questions and holistic model
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- Acquire researcher needs associated with research
activities based on CVs and activity logs
- Identification of researcher roles:
- Researcher
- Research group leader, PhD Advisor
- Event organizer, Volume editor, Journal board member
- Evaluator of publications, researchers, organizations/groups,
projects, and funding programs
- Research project proposer / manager
- Industry transfer mediator / recruiter
- For each group of roles we asked competency questions
and provided answers via academic terms and their
relationships
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5 - Competency questions and holistic model
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- What positions (in projects, or general) in other organizations may attract junior
researchers as an alternative to working in my group? (Research group leader)
- Topic - Project - Organization
- Topic - Position - Organization
- What has been researched / written on the topic this publication deals with? (Evaluators
of publications)
- Publication - Topic - Publication
- Publication - Topic - Project
- How important are the venues where the researcher publishes? (Evaluators of
researchers)
- Researcher - Publication Venue - Assessment
- How topical are the goals of the project, in terms of problems addressed? Do people
often write on these problems? Are they encouraged by funding programs? (Evaluators
of projects)
- Project - Goal/Problem - Publication - Researcher
- Project - Goal/Problem - Program
- Which company or other organization is active in the given field, as a potential industry
transfer target? (Industry transfer promotor)
- Project - Topic - Organization
The full list of competency questions is available on our GitHub repository
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5 - Competency questions and holistic model
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- Extract graph fragments from competency questions
- Create a glossary of terms and their hierarchies
- Map relationships to concept paths
- Create the overall high-level holistic conceptual model
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5 - Competency questions and holistic model
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- We created and populated a spreadsheet with concepts,
their subtypes and entity-relationship paths
(https://bit.ly/3ajj99T)
- For each concept and relationship, we determined whether
it is covered in each ontology and by which classes and
properties in the ontology, in an approximated manner
- The exploration of ontologies can be documentation-based
or via source code (if available)
- We aggregated the number of covered concepts for each
ontology and the number of appearances of each concept
in each ontology
- We identified missing features in each ontology and
coverage overlaps across these ontologies
6 - Ontology-model coverage
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6 - Ontology-model coverage
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The full coverage table is available on our GitHub repository
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- The research-related concepts are numerous and very
well-covered by existing ontologies when combined
- Underdevelopment of concepts: “spin-offs”, “funding
programs” and some forms of “assessment”
- Missing a unifying superclass, e.g. “reusable artifact”
6 - Ontology-model coverage - observations
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- The comparison of the ontologies vs. the holistic model
reveals a high number of overlaps in many areas while
some others are left nearly untouched
- Future work:
- extending the survey to KGs and thesauri
- re-use of ontologies in datasets
7 - Conclusions and future work
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