Linkflows: Enabling a Web of Linked Semantic Publishing Workflows

  • Cristina-Iulia BucurEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11155)


In recent decades, the prevalence of the Internet and Semantic Web technologies has shifted the traditional scientific journal publishing framework towards the digital environment. In support of this, ontologies on digital publishing and new forms of granular provenance modeling have been built to support digital publishing. These fine-grained technologies facilitate the decomposition of traditional science articles in constituent machine-readable parts that are linked not only with one another, but also to other related fine-grained parts of knowledge on the Web following the Linked Data principles. However, these resulting digital artifacts of fine-grained knowledge are static objects that do not take dynamic processes, or scientific workflows, into account. Additionally, scientific workflows are important because they directly produce and consume digital artifacts. In this project, we enable the decentralized execution of scientific workflows of digital artifacts across platforms such that individual steps of single workflows can be distributed. By considering these scientific workflows, we can further find new dimensions with respect to the quality and impact of digital artifacts. In our preliminary results we have developed a model that is able to support Linked Data Notifications to demonstrate the feasibility of our approach.


Digital publishing workflows Scientific workflows Semantic publishing Semantic web 



We would like to thank Tobias Kuhn, Davide Ceolin, Lora Aroyo, Johan Oomen, Erwin Verbruggen, Maarten Frohlich and Stephanie Delbecque for helping in writing this research proposal, for their valuable and constant feedback and ideas.


  1. 1.
    Budapest Open Access Initiative.
  2. 2.
  3. 3.
  4. 4.
    Linked Data Notifications.
  5. 5.
    OWL Web Ontology Language for Services (OWL-S).
  6. 6.
  7. 7.
    PROV-O: The PROV Ontology.
  8. 8.
  9. 9.
    Web Annotaion Data Model.
  10. 10.
    Mons, B.: Which gene did you mean? BMC Bioinform. 6, 142 (2005). Scholar
  11. 11.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked Data - the story so far. Int. J. Semant. Web Inf. 5(3), 1–22 (2009). Scholar
  12. 12.
    Mazieres, D., Frans Kaashoek, M.: Escaping the evils of centralized control with self-certifying pathnames. In: Proceedings of the 8th ACM SIGOPS European Workshop on Support for Composing Distributed Applications, pp. 118–125 (1998)Google Scholar
  13. 13.
    Shotton, D.: Semantic publishing: the coming revolution in scientific journal publishing. Learn. Publ. 22(2), 85–94 (2009). Scholar
  14. 14.
    Dissecting our impact factor. In: Nature Materials (2011).
  15. 15.
    Garfield, E.: The history and meaning of the journal impact factor. JAMA 295(1), 90–93 (2006). Scholar
  16. 16.
    Taylor, I.J., Deelman, E., Gannon, D.B., Shields, M.: Workflows for e-Science: Scientific Workflows for Grids. Springer, London (2014). ISBN: 1849966192Google Scholar
  17. 17.
    Filali, I., Bongiovanni, F., Huet, F., Baude, F.: A survey of structured P2P systems for RDF data storage and retrieval. In: Hameurlain, A., Küng, J., Wagner, R. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems III. LNCS, vol. 6790, pp. 20–55. Springer, Heidelberg (2011). Scholar
  18. 18.
    Debattista, J., Lange, C., Auer, S.: daQ, an ontology for dataset quality information. In: Proceedings of the Workshop on Linked Data on the Web 1184 (2014)Google Scholar
  19. 19.
    Mesirov, J.P.: Accessible reproducible research. Int. J. Semant. Web Inf. 327(5964), 415–416 (2010). Scholar
  20. 20.
    Cohen, J.P., Lo, H.Z.: Academic torrents: a community-maintained distributed repository. In: Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment (2014).
  21. 21.
    Janowicz, K., Hitzler, P.: Open and transparent: the review process of the Semantic Web journal. Learn. Publ. 25, 48–55 (2012). Scholar
  22. 22.
    Wilkinson, M., et al.: The FAIR Guiding Principles for scientific data management and stewardship. Scie. Data 3 (2016).
  23. 23.
    Baker, M.: 1,500 scientists lift the lid on reproducibility. Nature 533(7604) (2016).
  24. 24.
    Murray-Rust, P.: Open data in science. Ser. Rev. 34(1), 52–64 (2008). Scholar
  25. 25.
    Bechhofer, S., et al.: Why linked data is not enough for scientists. Future Gener. Comput. Syst. 29(2), 599–611 (2013). Scholar
  26. 26.
    Peroni, S.: Automating semantic publishing. Data Sci. J. (2017).
  27. 27.
    Peroni, S.: The semantic publishing and referencing ontologies. In: Semantic Web Technologies and Legal Scholarly Publishing, pp. 121–193 (2014).
  28. 28.
    Kiesslich, T., Weineck, S.B., Koelblinger, D.: Reasons for journal impact factor changes: influence of changing source items. PLOS One (2016).
  29. 29.
    Kuhn, T., Dumontier, M.: Trusty URIs: verifiable, immutable, and permanent digital artifacts for linked data. In: Proceedings of the 11th Extended Semantic Web Conference (2014).
  30. 30.
    Kuhn, T., et al.: Decentralized provenance-aware publishing with nanopublications. In: PeerJ Comput. Sci. (2016).

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceVrije Universiteit AmsterdamAmsterdamThe Netherlands

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