{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T08:40:07Z","timestamp":1741941607930,"version":"3.38.0"},"reference-count":10,"publisher":"China Science Publishing & Media Ltd.","issue":"1","content-domain":{"domain":["www.mitpressjournals.org"],"crossmark-restriction":true},"short-container-title":["Data Intelligence"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:p> Federated Research Data Infrastructures aim to provide seamless access to research data along with services to facilitate the researchers in performing their data management tasks. During our research on Open Science (OS), we have built cross-disciplinary federated infrastructures for different types of (open) digital resources: Open Data (OD), Open Educational Resources (OER), and open access documents. In each case, our approach targeted only the resource \u201cmetadata\u201d. Based on this experience, we identified some challenges that we had to overcome again and again: lack of (i) harvesters, (ii) common metadata models and (iii) metadata mapping tools. In this paper, we report on the challenges we faced in the federated infrastructure projects we were involved with. We structure the report based on the three challenges listed above. <\/jats:p>","DOI":"10.1162\/dint_a_00080","type":"journal-article","created":{"date-parts":[[2021,1,14]],"date-time":"2021-01-14T14:44:31Z","timestamp":1610635471000},"page":"79-87","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":3,"title":["On the Complexities of Federating Research Data Infrastructures"],"prefix":"10.3724","volume":"3","author":[{"given":"Atif","family":"Latif","sequence":"first","affiliation":[{"name":"24105 Kiel, Duesternbrooker Weg 120, Germany"}]},{"given":"Fidan","family":"Limani","sequence":"additional","affiliation":[{"name":"24105 Kiel, Duesternbrooker Weg 120, Germany"}]},{"given":"Klaus","family":"Tochtermann","sequence":"additional","affiliation":[{"name":"24105 Kiel, Duesternbrooker Weg 120, Germany"}]}],"member":"2026","reference":[{"key":"ref1","unstructured":"[1] Collins, S., et al. Turning FAIR into reality: Final report and action plan from the European Commission expert group on FAIR data. Available at: https:\/\/ec.europa.eu\/info\/sites\/info\/files\/turning_fair_into_reality_1.pdf. Accessed 30 October 2020"},{"key":"ref2","unstructured":"[2] Open Science. European Commission research and innovation. Available at: https:\/\/ec.europa.eu\/info\/sites\/info\/files\/research_and_innovation\/knowledge_publications_tools_and_data\/documents\/ec_rtd_factsheet-open-science_2019.pdf. Accessed 30 October 2020"},{"key":"ref3","unstructured":"[3] Wilkinson, M., et al. The FAIR guiding principles for scientific data management and stewardship. Scientific Data 3, Article No. 160018 (2016)"},{"key":"ref4","unstructured":"[4] Goldstein, S.: The evolving landscape of Federated Research Data Infrastructures. Available at: http:\/\/doi.org\/10.5281\/zenodo.1064730. Accessed 30 October 2020"},{"issue":"1","key":"ref5","doi-asserted-by":"crossref","first-page":"17","DOI":"10.5334\/dsj-2019-017","volume":"18","author":"Latif A.","year":"2019","journal-title":"Data Science Journal"},{"key":"ref6","unstructured":"[6] van de Sompel, H. Overview of ResourceSync. Available at: https:\/\/www.niso.org\/standards-committees\/resourcesync. Accessed 17 December 2020"},{"key":"ref7","unstructured":"[7] RISK, U.: Draft standard for learning object metadata. IEEE Report number: 1484.12.4 (2002)"},{"issue":"1","key":"ref8","first-page":"15","volume":"40","author":"Waters J.K.","year":"2013","journal-title":"Technological Horizons in Education"},{"key":"ref9","unstructured":"[9] Broeder, D., et al. Standardizing a component metadata infrastructure. In: LREC 2012: The 8th International Conference on Language Resources and Evaluation, pp. 1387\u20131390 (2012)"},{"key":"ref10","unstructured":"[10] Metadata Standards Directory WG. Available at: https:\/\/www.rd-alliance.org\/groups\/metadata-standards-directory-working-group.html. Accessed 30 October 2020"}],"container-title":["Data Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/dint_a_00080","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T07:41:54Z","timestamp":1741938114000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciengine.com\/doi\/10.1162\/dint_a_00080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2]]},"references-count":10,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["10.1162\/dint_a_00080"],"URL":"https:\/\/doi.org\/10.1162\/dint_a_00080","relation":{},"ISSN":["2641-435X"],"issn-type":[{"type":"electronic","value":"2641-435X"}],"subject":[],"published":{"date-parts":[[2021,2]]},"assertion":[{"value":"2021-02-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}