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Cited by 4

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A Framework for Citing Nanopublications

Fabris, Erika, Kuhn, Tobias, Silvello, Gianmaria·2019·Lecture Notes in Computer Science
DOI 10.1007/978-3-030-30760-8_6
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Overview

Integrity signals

Registry

Crossref · 10.1007/978-3-030-30760-8_6

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 24

  1. Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data, vol. 12. CODATA-ICSTI Task Group on Data Citation Standards and Practices, September 2013 · DOI
  2. Alawini, A., Davidson, S.B., Silvello, G., Tannen, V., Wu, Y.: Data citation: a new provenance challenge. IEEE Data Eng. Bull. 41(1), 27–38 (2018)
  3. Borgman, C.L.: Big Data, Little Data, No Data. MIT Press, Cambridge (2015) · DOI
  4. Buneman, P., Davidson, S.B., Frew, J.: Why data citation is a computational problem. Commun. ACM (CACM) 59(9), 50–57 (2016) · DOI
  5. Candela, L., Castelli, D., Manghi, P., Tani, A.: Data journals: a survey. J. Assoc. Inf. Sci. Technol. 66(9), 1747–1762 (2015) · DOI
  6. Carroll, J., Bizer, C., Hayes, P., Stickler, P.: Semantic web publishing using named graphs. In: Proceedings of the ISWC 2004 Workshop on Trust, Security, and Reputation on the Semantic Web. CEUR Workshop Proceedings, vol. 127. CEUR-WS.org (2004)
  7. Davidson, S.B., Buneman, P., Deutch, D., Milo, T., Silvello, G.: Data citation: a computational challenge. In: Proceedings of the 36th ACM Symposium on Principles of Database Systems, PODS 2017, pp. 1–4. ACM Press (2017) · DOI
  8. Gibson, A.P., van Dam, J.C.J., Schultes, E., Roos, M., Mons, B.: Towards computational evaluation of evidence for scientific assertions with nanopublications. In: Proceedings of the 5th International Workshop on Semantic Web Applications and Tools for Life Sciences (2012)
  9. Golden, P., Shaw, R.: Period assertion as nanopublication: the PeriodO period gazetteer. In: Proceedings of the 24th International Conference on World Wide Web, WWW 2015 Companion, pp. 1013–1018. ACM Press (2015) · DOI
  10. Green, T.: We need publishing standards for datasets and data tables. Technical report. OECD Publishing (2010) · DOI
  11. Groth, P., Gibson, A., Velterop, J.: The anatomy of a nanopublication. Inf. Serv. Use 30(1–2), 51–56 (2010) · DOI · Paper page
  12. Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool Publishers, San Rafael (2011) · DOI
  13. Hey, T., Tansley, S., Tolle, K. (eds.): The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, Redmond (2009)
  14. Kuhn, T.: nanopub-java: a Java library for nanopublications. In: Proceedings of the 5th Workshop on Linked Science 2015 co-located with (ISWC 2015). CEUR Workshop Proceedings, vol. 1572, pp. 19–25. CEUR-WS.org (2015)
  15. Kuhn, T., et al.: Nanopublications: a growing resource of provenance-centric scientific linked data. In: 14th IEEE International Conference on e-Science, pp. 83–92. IEEE Computer Society (2018) · DOI · Paper page
  16. Kuhn, T., Willighagen, E., Evelo, C., Queralt-Rosinach, N., Centeno, E., Furlong, L.I.: Reliable granular references to changing linked data. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 436–451. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68288-4_26 · DOI
  17. Mons, B., et al.: The value of data. Nat. Genetics 43(4), 281–283 (2011) · DOI
  18. Piñero, J., et al.: DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res. 45(D1), D833–D839 (2017) · DOI · Paper page
  19. Queralt-Rosinach, N., Piñero, J., Bravo, À., Sanz, F., Furlong, L.: DisGeNET-RDF: harnessing the innovative power of the semantic web to explore the genetic basis of diseases. Bioinformatics 32(14), 2236–2238 (2016) · DOI
  20. Rauber, A., Ari, A., van Uytvanck, D., Pröll, S.: Identification of reproducible subsets for data citation, sharing and re-use. Bull. IEEE Techn. Comm. Digit. Libr. Spec. Issue Data Cit. 12(1), 6–15 (2016)
  21. Silvello, G.: Learning to cite framework: how to automatically construct citations for hierarchical data. J. Assoc. Inf. Sci. Technol. (JASIST) 68(6), 1505–1524 (2017) · DOI
  22. Silvello, G.: Theory and practice of data citation. J. Assoc. Inf. Sci. Technol. (JASIST) 69(1), 6–20 (2018) · DOI
  23. Starr, J., Gastl, A.: isCitedBy: a metadata scheme for DataCite. D-Lib Mag. 17(1/2) (2011) · DOI
  24. Wu, Y., Alawini, A., Davidson, S.B., Silvello, G.: Data citation: giving credit where credit is due. In: Proceedings of the 2018 International Conference on Management of Data, SIGMOD Conference 2018, pp. 99–114. ACM Press (2018) · DOI

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Metadata

Authors
Fabris, E., Kuhn, T., & Silvello, G.
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2019
Pages
70-83
ISSN
  • 0302-9743
  • 1611-3349
DOI
10.1007/978-3-030-30760-8_6
Cited by
4
References
1
Language
en
Licence
www.springer.com/tdm (tdm)

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 ›

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