FDO Papers

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References

A curated list of foundational papers, reports, and specifications that underpin the theory and practice of FAIR Digital Objects.

2006

A framework for distributed digital object services Kahn, R., & Wilensky, R. (2006) International Journal on Digital Libraries, 6(2), 115–123 https://doi.org/10.1007/s00799-005-0128-x

2015

Data Foundation and Terminology Work Group Products Berg-Cross, G., Ritz, R., & Wittenburg, P. (2015) https://doi.org/10.15497/06825049-8CA4-40BD-BCAF-DE9F0EA2FADF

2016

Automated schema extraction for PID information types Schwardmann, U. (2016) 2016 IEEE International Conference on Big Data (Big Data), 3036–3044 https://doi.org/10.1109/BigData.2016.7840957

2018

Common Patterns in Revolutionary Infrastructures and Data Peter Wittenburg, G. S. (2018) https://doi.org/10.23728/B2SHARE.4E8AC36C0DD343DA81FD9E83E72805A0

Digital Object Interface Protocol Specification DONA Foundation (2018) https://www.dona.net/sites/default/files/2018-11/DOIPv2Spec_1.pdf

Turning FAIR into Reality Final report and action plan from the European Commission expert group on FAIR data European Commission: Directorate-General for Research and Innovation (2018) https://op.europa.eu/en/publication-detail/-/publication/7769a148-f1f6-11e8-9982-01aa75ed71a1/language-en

2019

FAIR Principles and Digital Objects: Accelerating Convergence on a Data Infrastructure Schultes, E., & Wittenburg, P. (2019) In Y. Manolopoulos & S. Stupnikov (Eds.), Data Analytics and Management in Data Intensive Domains (Vol. 1003, pp. 3–16). Springer International Publishing. https://doi.org/10.1007/978-3-030-23584-0_1

FAIR Digital Objects – Collection of documents GEDE (2019) https://github.com/GEDE-RDA-Europe/GEDE/tree/master/FAIR%20Digital%20Objects

2020

FAIR Data and Services in Biodiversity Science and Geoscience Lannom, L., Koureas, D., & Hardisty, A. R. (2020) Data Intelligence, 2(1–2), 122–130 https://doi.org/10.1162/dint_a_00034

Digital Objects – FAIR Digital Objects: Which Services Are Required? Schwardmann, U. (2020) Data Science Journal, 19, 15 https://doi.org/10.5334/dsj-2020-015

Making Data and Workflows Findable for Machines Weigel, T., Schwardmann, U., Klump, J., Bendoukha, S., & Quick, R. (2020) Data Intelligence, 2(1–2), 40–46 https://doi.org/10.1162/dint_a_00026

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units De Smedt, K., Koureas, D., & Wittenburg, P. (2020) Publications, 8(2), 21 https://doi.org/10.3390/publications8020021

Persistent Identification of Instruments Stocker, M., Darroch, L., Krahl, R., Habermann, T., Devaraju, A., Schwardmann, U., D’Onofrio, C., & Häggström, I. (2020) Data Science Journal, 19, 18 https://doi.org/10.5334/dsj-2020-018