The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Improving Access to Scientific Literature with Knowledge Graphs
Abstract
The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based-formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this article, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1,500 scientists lift the lid on reproducibility
Baker, M. (2016) · Nature · doi:10.1038/533452a · Cited by 4,209
Flagged first, then by citations
Research works printed but not linked: 8
- Ammar, W.; Groeneveld, D.; Bhagavatula, C.; Beltagy, I.; Crawford, M.; Downey, D.; Dunkelberger, J.; Elgohary, A.; Feldman, S.; Ha, V.A.; Kinney, R.M.; Kohlmeier, S.; Lo, K.; Murray, T.C.; Ooi, H.; Peters, M. E.; Power, J.L.; Skjonsberg, S.; Wang, L.L.; Wilhelm, C.; Yuan, Z.; Zuylen, M.V.; Etzioni, O. (2018): Construction of the Literature Graph in Semantic Scholar. NAACL-HLT. · DOI · Paper page
- Brack, A.; D’Souza, J.; Hoppe, A.; Auer, S.; Ewerth, R. (2020): Domain-Independent Extraction of Scientific Concepts from Research Articles. In: European Conference on Information Retrieval ECIR, (1), 251–66. · DOI
- Corrêa, A.S.; Zander, P.O. (2017): Unleashing tabular content to open data: A survey on pdf table extraction methods and tools. In: Proceedings of the 18th Annual International Conference on Digital Government Research, 54–63. · DOI
- Jaradeh, M. Y.; Stocker, M.; Auer, S. (2020): Question Answering on Scholarly Knowledge Graphs. In: 24th International Conference on Theory and Practice of Digital Libraries (TPDL 2020), 19–32. · DOI
- Lopez, P. (2009): GROBID: Combining automatic bibliographic data recognition and term extraction for scholarship publications. In: International conference on theory and practice of digital libraries, 473–74. Berlin, Heidelberg: Springer. · DOI
- Oelen, A.; Jaradeh, M. Y.; Stocker, M.; Auer, S. (2020a): Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. In: JCDL ’20: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020, 97–106. Available at https://doi.org/10.1145/3383583.3398520. · DOI
- Oelen, A.; Stocker, M.; Auer, S. (2020b): Creating a Scholarly Knowledge Graph from Survey Article Tables. In: ICADL ’20: The 22nd International Conference on Asia-Pacific Digital Libraries (in press). · DOI · Paper page
- Sinha, Arnab; Shen, Zhihong; Song, Yang; Ma, Hao; Eide, Darrin; Hsu, Bo-June (Paul); Wang, Kuansan (2015): An Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, USA, 243–46. Available at http://dx.doi.org/10.1145/2740908.2742839. · DOI
Cited by
Sorted by citations
Nechakhin, V., D’Souza, J., & Eger, S. (2024) · Information · doi:10.3390/info15060328 · Cited by 17
Self-citationAuer, S., Stocker, M., Karras, O., Oelen, A., D'Souza, J., & Lorenz, A.-L. (2023) · Proceedings of the Conference on Research Data Infrastructure · doi:10.52825/cordi.v1i.272 · Cited by 3
Self-citationYESciEval: Robust LLM-as-a-Judge for Scientific Question Answering
D'Souza, J., Giglou, H. B., & Münch, Q. (2025) · arXiv · doi:10.48550/arxiv.2505.14279
Self-citation
Metadata
- Authors
- Auer, S., Oelen, A., Haris, M., Stocker, M., D’Souza, J., Farfar, K. E., Vogt, L., Prinz, M., Wiens, V., & Jaradeh, M. Y.
- Venue
- Bibliothek Forschung und Praxis
- Publisher
- Walter de Gruyter GmbH
- Published
- 2020-11-30
- Volume
- 44
- Issue
- 3
- Pages
- 516-529
- ISSN
- 1865-7648
- 0341-4183
- Cited by
- 82
- References
- 1
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
