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Towards Semantic Integration of Federated Research Data

  • Javad ChamanaraEmail author
  • Angelina Kraft
  • Sören Auer
  • Oliver Koepler
Schwerpunktbeitrag
  • 32 Downloads

Abstract

Digitization of the research (data) lifecycle has created a galaxy of data nodes that are often characterized by sparse interoperability. With the start of the European Open Science Cloud in November 2018 and facing the upcoming call for the creation of the National Research Data Infrastructure (NFDI), researchers and infrastructure providers will need to harmonize their data efforts. In this article, we propose a recently initiated proof-of-concept towards a network of semantically harmonized Research Data Management (RDM) systems. This includes a network of research data management and publication systems with semantic integration at three levels, namely, data, metadata, and schema. As such, an ecosystem for agile, evolutionary ontology development, and the community-driven definition of quality criteria and classification schemes for scientific domains will be created. In contrast to the classical data repository approach, this process will allow for cross-repository as well as cross-domain data discovery, integration, and collaboration and will lead to open and interoperable data portals throughout the scientific domains.

At the joint lab of L3S research center and TIB Leibniz Information Center for Science and Technology in Hanover, we are developing a solution based on a customized distribution of CKAN called the Leibniz Data Manager (LDM). LDM utilizes the CKAN’s harvesting functionality to exchange metadata using the DCAT vocabulary. By adding the concept of semantic schema to LDM, it will contribute to realizing the FAIR paradigm. Variables, their attributes and relationships of a dataset will improve findability and accessibility and can be processed by humans or machines across scientific domains. We argue that it is crucial for the RDM development in Germany that domain-specific data silos should be the exception, and that a semantically-linked network of generic and domain-specific research data systems and services at national, regional, and organization levels should be promoted within the NFDI initiative.

Keywords

Semantic interoperation Ontology development (Meta)Data harmonization 

References

  1. 1.
    Ayris P, Berthou JY, Bruce R, Lindstaedt S, Monreale A, Mons B, Murayama Y, Södergård C, Tochtermann K, Wilkinson R (2016) Realising the European open science cloud. European Union. https://ec.europa.eu/research/openscience/pdf/realising_the_european_open_science_cloud_2016.pdf  https://doi.org/10.2777/940154 Google Scholar
  2. 2.
    Bijsterbosch M, Duca D, Katerbow M, Kupiainen I, Dillo I, Doorn P, Enke H, de Lucas JEM (2016) Funding research data management and related infrastructures: knowledge exchange and science europe briefing paperGoogle Scholar
  3. 3.
    Diepenbroek M, Glöckner FO, Grobe P, Güntsch A, Huber R, König-Ries B, Kostadinov I, Nieschulze J, Seeger B, Tolksdorf R, Triebel D (2014) Towards an integrated biodiversity and ecological research data management and archiving platform: the german federation for the curation of biological data (gfbio). In: Plödereder E, Grunske L, Schneider E, Ull D (eds) Informatik 2014. Gesellschaft für Informatik e.V., Bonn, pp 1711–1721Google Scholar
  4. 4.
    Flemons P, Guralnick R, Krieger J, Ranipeta A, Neufeld D (2007) A web-based GIS tool for exploring the world’s biodiversity: The Global Biodiversity Information Facility Mapping and Analysis Portal Application (GBIF-MAPA). Ecol Inform 2(1):49–60.  https://doi.org/10.1016/j.ecoinf.2007.03.004 (http://www.sciencedirect.com/science/article/pii/S1574954107000106)CrossRefGoogle Scholar
  5. 5.
    Gerlach R, Blaa D, Chamanara J, Hohmuth M, Navabpour N, Thiel S, König-Ries B (2015) Bexis 2: A platform for managing heterogeneous biodiversity data and projects. In: TDWG 2015 Annual ConferenceGoogle Scholar
  6. 6.
    Grunzke R, Adolph T, Biardzki C, Bode A, Borst T, Bungartz HJ, Busch A, Frank A, Grimm C, Hasselbring W, Kazakova A, Latif A, Limani F, Neumann M, de Sousa NT, Tendel J, Thomsen I, Tochtermann K, Müller-Pfefferkorn R, Nagel WE (2017) Challenges in creating a sustainable generic research data infrastructure. Softwaretech Trends 37(2):74–77 (http://oceanrep.geomar.de/38756/)Google Scholar
  7. 7.
    Halilaj L, Grangel-González I, Coskun G, Lohmann S, Auer S (2016) Git4Voc: collaborative vocabulary development based on git. Int J Semant Comput 10(2):167–192.  https://doi.org/10.1142/S1793351X16400067 CrossRefGoogle Scholar
  8. 8.
    Halilaj L, Petersen N, Grangel-González I, Lange C, Auer S, Coskun G, Lohmann S (2016) Vocol: an integrated environment to support version-controlled vocabulary development. In: Knowledge Engineering and Knowledge Management - 20th International Conference, EKAW 2016 Bologna, 19.11.-23.11. 2016. Proceedings, pp 303–319  https://doi.org/10.1007/978-3-319-49004-5_20 Google Scholar
  9. 9.
    Karam N, Lorenz RH, Müller-Birn C (2017) The gfbio terminology service: enabling research data management beyond data heterogeneity. (Tage 2017), p 75Google Scholar
  10. 10.
    Martone ME (2015) FORCE11: building the future for research communications and e‑scholarship. Bioscience 65(7):635–635.  https://doi.org/10.1093/biosci/biv095 CrossRefGoogle Scholar
  11. 11.
    Michener WK, Allard S, Budden A, Cook RB, Douglass K, Frame M, Kelling S, Koskela R, Tenopir C, Vieglais DA (2012) Participatory design of DataONE-Enabling cyberinfrastructure for the biological and environmental sciences. Ecol Inform 11:5–15.  https://doi.org/10.1016/j.ecoinf.2011.08.007 (http://www.sciencedirect.com/science/article/pii/S1574954111000768)CrossRefGoogle Scholar
  12. 12.
    Mons B, Neylon C, Velterop J, Dumontier M, da Silva SLOB, Wilkinson MD (2017) Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud. Inf Serv Use 37(1):49–56.  https://doi.org/10.3233/ISU-170824 CrossRefGoogle Scholar
  13. 13.
    Romary L, Chambers S (2014) DARIAH: Advancing a digital revolution in the arts and humanities across Europe. e‑data&research. https://hal.inria.fr/hal-00913691. Accessed: 9 April 2019Google Scholar
  14. 14.
    Tochtermann K (2018) GO FAIR – Eine Initiative zum fairen Umgang mit Forschungsdaten. In: TK 7: lehren & unterstützen / Forschungsdatenmanagement International 14.6.2018Google Scholar
  15. 15.
    Widmann H, Thiemann H (2016) EUDAT B2FIND : a cross-discipline metadata service and discovery portal. In: EGU General Assembly Conference Abstracts, vol 18, p EPSC2016–8562Google Scholar
  16. 16.
    Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva SLB, Bourne PE (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3.  https://doi.org/10.1038/sdata.2016.18 CrossRefGoogle Scholar
  17. 17.
    Williams AJ, Harland L, Groth P, Pettifer S, Chichester C, Willighagen EL, Evelo CT, Blomberg N, Ecker G, Goble C, Mons B (2012) Open PHACTS: semantic interoperability for drug discovery. Drug Discov Today 17(21):1188–1198.  https://doi.org/10.1016/j.drudis.2012.05.016 (http://www.sciencedirect.com/science/article/pii/S1359644612001936)CrossRefGoogle Scholar

Copyright information

© Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Technische Informationsbibliothek (TIB)HanoverGermany

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