Hej alla,
Nu har vi avslutat vårt projekt kring tillgängliggörande av forskningsdata som haft ett fokus på forskarinvolvering. Slutrapporten från projektet "Tillgängliggörande av forskningsdata - lokal funktion för arbetet gentemot Svensk Nationell Datatjänst" är bifogad. Återkom gärna med frågor och kommentarer, men inte förrän i slutet av juli :)
Trevlig sommar!
Jonas
Jonas Fransson, PhD
Utvecklare av forskningsstöd / Coordinator Research Support Services
Malmö universitetsbibliotek / Malmö University Library
+46 (0)40 66 57 603 / +46 (0)72 234 94 17
jonas.fransson at mau.se<mailto:jonas.fransson at mau.se>
Hej!
Det finns fortfarande platser kvar till FAIR data steward-kursen i Uppsala 30 mars till 3 april 2020.
Registrering här: http://bit.ly/FAIRds-Nordic-SE
Hälsningar Monica
Monica Lassi, Fil. Dr.
IT-arkitekt
LUNARC, Centrum för vetenskapliga och tekniska beräkningar vid Lunds universitet
Besöksadress: V-huset LTH, entré G2, John Ericssons väg 1, Lund
Postadress: LUNARC, LTH, Lunds universitet, Box 118, 221 00 Lund
Mobil: +46 (0)70-647 10 91 | Tel: +46 (0)46-222 01 06
monica.lassi at lunarc.lu.se<mailto:monica.lassi at lunarc.lu.se>
När du skickar e-post till Lunds universitet behandlar vi dina personuppgifter i enlighet med gällande lagstiftning. Mer om hur dina personuppgifter behandlas hittar du på Lunds universitets webbplats: www.lu.se/integritet<http://www.lu.se/integritet>
Från: wp4 at eosc-nordic.eu <wp4 at eosc-nordic.eu> För Andreas Jaunsen
Skickat: den 15 januari 2020 14:00
Till: wp4 at eosc-nordic.eu
Ämne: [WP4] Nordic FAIR data stewardship course March 30 - April 3
Dear WP4 members,
We still have available space at the upcoming FAIR data stewardship course. Please consider to join this valuable course and distribute this among your institutions and preferably as broadly as possible among communities in the Nordic+Baltics!
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Registration to the third Nordic course on "FAIR Data Stewardship”, hosted and sponsored by Nordforsk/NeIC<http://www.neic.no/> and SNIC<http://www.snic.se/> + SND<http://www.snd.gu.se/> in Sweden, is open.
The event takes place in Uppsala, Sweden on 30 March - 3 April 2020.
To register follow this link: http://bit.ly/FAIRds-Nordic-SE
Early bird registration with a discounted fee of NOK 6750,- is still open until Feb 16, at which point it increases to NOK 8500,-
This is a fully fledged 5-day training event which will provide the much needed foundational skills for competent data stewards and data managers in the Nordic countries with knowledge of the FAIR principles and their application. This course is aimed at librarians or data experts whose work it is to facilitate sharing and re-use of research data. The course will be held by trainers from GO-FAIR and provides a broad introduction to data stewardship. Registration will be limited to max 35 persons and the course is subsidised by the hosting organisations (www.neic.no<http://www.neic.no/>, www.snic.se<http://www.snic.se/>, www.snd.gu.se<http://www.snd.gu.se/>).
Kind regards,
Andreas
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Overview
FAIR Data Stewardship, as a new profession, is rapidly gaining momentum. New requirements from national and international funders are driving the need for training of competent, professional data stewards and data managers with knowledge of the FAIR principles and their application. This course introduces the required knowledge and skills in a broader data stewardship context, including topics like semantic data modeling, metadata modeling, the FAIRification process, publishing FAIR Data Points, and other topics related to managing research project's data requirements. After completion of the course participants will be able to work with domain specialists in making their data FAIR and preserving them for re-use.
Who should attend
This course is aimed at librarians or data experts at universities, research institutions and research support centres who are dealing with the ever growing complexity of data integration. Currently data technicians/ICTers spend between 70 and 80 percent of their time on data wrangling such as dealing with data selection & retrieval, format issues, identifiers, ontologies, massaging the data so that it is ready for big data analysis. For large organisations choosing to GO FAIR, integration and re-use of data sets becomes less labor intensive, leaving more time to dive into more complex data analysis answering research questions.
