From the CTS application:
The repository has adequate funding and sufficient numbers of qualified staff managed through a clear system of governance to effectively carry out the mission.
The Dataverse community’s open source and transparent culture encourages the sharing of administrative and technical expertise, which can supplement the expertise of data collection staff, using multiple communication channels, include a public Dataverse Community forum on Google Groups, a public GitHub issues tracker, a public IRC channel, and Dataverse conferences, including the annual Dataverse Community Meeting.
Collection support staff of Dataverse repositories join a free and growing informal network of communities who use the Dataverse software and contribute data management expertise and development resources to improve the software. Members of the community can also become paying members of the Global Dataverse Community Consortium, which aims to provide a collaborative venue for institutions to leverage economies of scale in support of Dataverse repositories around the world.
Answers from successful applicants
Tilburg University Dataverse collection:
The repository is managed by Tilburg University’s Research Data Office, which operates under the department Research Support of Library and IT Services (LIS). The Research Data Office consists of a dedicated data team that carries out the mission on research data support of LIS. This team consists of two data librarians, a Research Data Officer and functional application managers.
The FTE available for the Research Data Office is 2,4 on a structural basis:
- Data librarians 1,3 FTE
- Research Data Officer 0,9 FTE
- Additional functional application manager from the Research Support department 0,1 FTE
- Head of department 0,1 FTE
On a temporary basis the Research Data Office makes use of two student workers for reviewing data packages (0,3 FTE per week from March until July 2018).
- Data librarians – the two data librarians of the Research Data Office are information specialists by profession with a background in Library and Information Science. One information specialist also has a Master of Arts degree and obtained the certificate ‘Data Intelligence for Librarians’ (May 22, 2013), a four day training course organized by DANS KNAW and 3TU.Datacentrum (now 4TU.Datacentrum). She is a member of the Research Data Alliance. The other information specialist is also a functional application manager and is Tilburg University’s representative in the national application manager committee for DataverseNL. Additionally, he is GDPR (General Data Protection Regulation) representative for Tilburg University Library & IT Services. He has followed education in law and in IT management.
- Research Data Officer - The Research Data Officer has a PhD in social sciences and worked in a previous position as a Research Data Officer at the Behavioural Science Institute of Radboud University. In this position she provided guidelines and support to researchers how to store, manage and archive research data. She has obtained the certificate ‘Essentials 4 Data Support’ (May-June 2017, full course, online + two days face-to-face).
- Students workers – the hired student workers will receive in-house training by the staff of the Research Data Office and on-site training visits at DANS.
The purpose of the research data team is to facilitate archiving, recording and dissemination of research data.
- The archiving of data sets in Tilburg University Dataverse
- Support with the archiving of datasets in other archives such as DANS EASY (http://www.dans.knaw.nl/en)
- Connect publications with the matching research data in the Tilburg University Repository
- Advising research departments in the preparation and implementation of a data management plan
More information on the organisational structure can be found at: https://www.tilburguniversity.edu/upload/ea60fda7-8387-4cd4-b1b8-28ab9b8952c8_LIS%20web.jpg
As a central unit of the university, the Research Data Office is fully funded by the university. The RDO holds a permanent role and budget within the organization. The head of the department as well as the team members participate in national working groups and network events in the field of data management and preservation. The planning of professional trainings, such as the DANS ‘Essentials 4 data’ training, are evaluated in yearly performance reviews of the staff.
QDR is housed in the Center for Qualitative and Multi-Method Inquiry (CQMI), a unit of the Maxwell School of Citizenship and Public Affairs, a nationally leading public policy school at Syracuse University. CQMI is also the home of the Consortium for Qualitative Research Methods (CQRM), which conducts an annual international Institute for Qualitative and Multi-methods Research with around 180 participants.
The repository is led by social scientists at Syracuse University and Georgetown University as well as information scientists at the University of Washington at Seattle:
Colin Elman, Professor of Political Science, Syracuse University.
Diana Kapiszewski, Associate Professor of Government, Georgetown University.
Carole Palmer, Professor and Associate Dean for Research, Information School, University of Washington, Seattle
Nic Weber, Assistant Professor, Information School, University of Washington, Seattle
QDR’s Associate Director and Curation Specialist assist users and curate deposits with the support of two graduate student assistants as well as part-time support from CQMI personnel.
QDR has a small team of developers (one frontend/database, one systems/dev-ops), building on a lightly customized version of the Dataverse open source development software to reduce development costs.
QDR staff regularly attend professional meetings to present their work and benefit from an international community of data specialists. Among conferences attended in the past two years are the annual meeting of the International Association of Social Science Information Services and Technology (IASSIST), Research Data Alliance (RDA), Dataverse Community Meetings, Research Data Access and Preservation Summit (RDAP), Preservation and Archiving Interest Group (PASIG), and the International Data Curation Conference (IDCC). QDR and/or its personnel are members and actively participate in international bodies including RDA, IASSIST, and DCC. One of QDR’s co-directors serves on the Center for Open Science’s Transparency and Openness Promotion (TOP) Guidelines Coordinating Committee and until recently a co-director served on ICPSR’s Governing Council. QDR’s Associate Director serves on the Technical Steering group of DataCite.
Funding for the repository currently comes from various sources:
Grant funding for core operations provided by the National Science Foundation (Political Science Program) Project-based funding by the Robert Wood Johnson Foundation
In-kind support by Syracuse University (office space, IT support, administrative support, graduate assistants)
Revenues from institutional membership and depositor support starting in July 2018. These are part of a long-term sustainability plan.
QDR has a robust, and increasing, user base. As of October 2018, QDR has over 1,400 registered users and the site receives an average of about 1,700 monthly unique users according to google analytics. Most users (ca. 70%) and visitors (ca 60%) are from the United States, but both groups include researchers from across the globe, spanning five continents.
Institutional Membership: https://qdr.syr.edu/membership/join
QDR Access: https://qdr.syr.edu/qdr-publications/qdr-access
3 – The repository is in the implementation phase
The organization of DataverseNO is described in the section Organization of DataverseNO  of the About page on the DataverseNO info site, and is discussed in detail below.
The organization, including repository structure, governance, data curation, and Designated Community, of DataverseNO is regulated in the following documents: Establishment of a Board for DataverseNO ; Mandate Board for DataverseNO ; Steering Document for DataverseNO ; DataverseNO Partner Agreements (attached to this application) including a data processor agreement; DataverseNO Policy Framework ; DataverseNO Administrator Guidelines ; DataverseNO Curator Guidelines ; DataverseNO Deposit Guidelines .
REPOSITORY STRUCTURE AND CONTENT
The repository structure of DataverseNO is discussed in R0. Below follows a brief overview of the collections in DataverseNO as of February 2020. For an updated overview, see the Support page  on the DataverseNO info site.
HVL Open Research Data
Institutional collection for Western Norway University of Applied Sciences. Collection launched in April 2019. No deposited datasets. Two collection managers.
INN Open Research Data
Institutional collection for Inland Norway University of Applied Sciences. Collection launched in May 2019. Two published and three unpublished datasets. Two collection managers.
NMBU Open Research Data
Institutional collection for Norwegian University of Life Sciences (NMBU). Collection launched in October 2018. Eight published and nine unpublished datasets from researchers working within the following subjects: Agricultural Sciences; Business and Management; Medicine, Health and Life Sciences. Two collection managers.
NORD Open Research Data
Institutional collection for Nord University. Collection launched in June 2019. No deposited datasets. Three collection managers.
NTNU Open Research Data
Institutional collection for NTNU - Norwegian University of Science and Technology. Collection launched in January 2019. Seven published and four unpublished datasets from researchers working within the following subjects: Earth and Environmental Sciences; Medicine, Health and Life Sciences; Physics. Four collection managers
UiA Open Research Data
Institutional collection for University of Agder. Collection launched in August 2017. Six published and two unpublished datasets from researchers working within the following subjects: Computer and Information Science; Engineering; Medicine, Health and Life Sciences; Social Sciences. Four collection managers
UiB Open Research Data
Institutional collection for University of Bergen. Collection launched in June 2019. Three published and seven unpublished datasets from researchers working within the following subjects: Arts and Humanities; Medicine, Health and Life Sciences; Physics; Computer and Information Science; Earth and Environmental Sciences; Social Sciences. Three collection managers.
UiS Open Research data
Institutional collection for University of Stavanger. Collection launched in January 2020. No deposited datasets. Two collection managers.
UiT Open Research Data
Institutional collection for UiT The Arctic University of Norway. Collection launched in September 2016. 578 published and 29 unpublished datasets from researchers working within the following subjects: Agricultural Sciences; Arts and Humanities; Astronomy and Astrophysics; Business and Management; Chemistry; Computer and Information Science; Earth and Environmental Sciences; Engineering; Mathematical Sciences; Medicine, Health and Life Sciences; Physics; Social Sciences. Eight collection managers.
TROLLing (The Tromsø Repository of Language and Linguistics)
Special collection for linguistic data and statistical code from linguists worldwide . Collection launched in June 2014. 80 published and 20 unpublished datasets. Two collection managers.
DataverseNO is a repository owned and operated by UiT The Arctic University of Norway, and offered as a service to other institutions, and to individual researchers from research institutions in Norway. UiT The Arctic University of Norway is part of the national, governmental higher education and research system, as one of currently ten state-owned universities under the ultimate responsibility of the Norwegian Ministry of Education and Research (see also section II Funding below).
The Board for DataverseNO has the overall responsibility for DataverseNO, with a mandate provided by the University Management of UiT The Arctic University of Norway .
Collections within DataverseNO may have their own advisory committees which give advice to the collection managers as well as to the Board of DataverseNO on high-level aspects of the operation and development of the collection at stake as well as the entire repository. Members of the Designated Community may raise any issues with representatives from the advisory committee of the collection at stake by contacting them directly. Currently, only TROLLing, a special collection in DataverseNO, has formally established an advisory committee, the TROLLing Scientific Advisory Board . The TROLLing Scientific Advisory Board provides their advice to the managers of TROLLing.
The operation of institutional collections is part of the research support services and the institutional management at the DataverseNO partner institutions. Partner institutions have well-established venues in place where research support units, such as the University Library, discuss issues with representatives from the different research communities at the institution. Feedback from such discussions is provided to the managers of the institutional collections. On their part, managers of institutional collections discuss advice and feedback from the user groups of their institutional collections in the Advisory Committee for DataverseNO. This committee, illustrated with the blue box in the middle of the GOVERNANCE section of the DataverseNO Organization Chart, consists of representatives from all DataverseNO partner institutions (usually the collection managers), and the managers of DataverseNO. The members of the DataverseNO Advisory Committee meet at least twice a year to discuss issues concerning the organization of DataverseNO, including governance, policies and guidelines, repository structure and operation (including functionality), data curation, and issues raised by the Designated Community. Requests and advice from the DataverseNO Advisory Committee are communicated to the Board of DataverseNO and to the managers of the institutional collections by the DataverseNO Repository Management.
The daily management and operation of DataverseNO are carried out by permanent staff from the Library, the IT department and the Research administration at UiT The Arctic University of Norway, as part of their ordinary tasks within their organization, based on defined responsibilities and roles agreed upon by the directors for the three organizational units, and approved by the university director.
The repository management of DataverseNO consists of three permanent staff members from the UiT Library. They are responsible for the management, maintenance, development and the daily operation of the repository, and they take care of the DataverseNO policies and guidelines, communication with the Board of DataverseNO, communication with and training of collection managers, the operation of the DataverseNO Advisory Committee, the configuration of the repository, establishment and configuration of institutional collections, user management, the implementation of new functionality and procedures to be used in the repository, preservation planning, and the certification of the repository. In addition, the DataverseNO repository management is responsible for the management of the top-level collection of the repository.
The technical operation and maintenance of the repository is carried out by two computer engineers from the UiT Library, and two computer engineers from the UiT IT department. The computer engineers at the library are responsible for the installation, customizing, and upgrading of the repository application. Note that the Dataverse application is only slightly customized for use in DataverseNO. The computer engineers at the IT department take care of the secure and sustainable operation, back-up, and upgrading of the servers used to run the repository application as well as of the customization and infrastructure used for federated authentication.
In addition, the management of DataverseNO involves one staff member from the Research administration at UiT, and one staff member from the IT department at UiT. They both work together with the service management. The staff member from the Research administration is responsible for the alignment of DataverseNO with the UiT policies and strategic framework, whereas the staff member from the IT department is responsible for the strategic development of IT infrastructure relevant to DataverseNO.
The managers of institutional collections within DataverseNO are responsible for the management and operation of the collection, including compliance of the institutional collection and underlying sub-collections with the DataverseNO policies and guidelines, user management of collection curators, training of and communication with collection curators, establishment and configuration of sub-collections, communication with DataverseNO repository management, communication with the management at the partner institution, representing the institutional collection in the DataverseNO Advisory Committee. The management of the institutional collections in DataverseNO are all Research Data Service staff members at the partner institutions. Each collection has at least two managers.
The managers of special collections have many of the same responsibilities as institutional collection managers, but limited to the thematic scope of the collection. They communicate with the advisory committee for the collection – if applicable. Currently, TROLLing is the only special collection in DataverseNO. TROLLing has two managers.
Curation of data deposited in institutional collections is the responsibility of the partner institutions, and is carried out by Research Data Service staff at these institutions. Datasets deposited in the top-level collection are curated by Research Data Service staff at UiT The Arctic University of Norway (owner of DataverseNO). Datasets deposited in special collections are curated by Research Data Service staff specialized in the subject(s) covered by the collection. Currently the only special collection, TROLLing, is curated by subject librarians for linguistics at UiT The Arctic University of Norway. All data curation in DatavereNO is carried out by staff members employed at the partner institutions. Typically, these data curators are mainly permanent staff working as subject librarians or as research support advisers at the library or in the different faculties and/or institutes at the DataverseNO partner institutions. Many of the data curators have PhD level education within the research disciplines for which they are providing support services. In addition, they have been, and are continuously, trained in research data management, and they have in-depth knowledge of data stewardship within the research disciplines they are set to support. Furthermore, they keep themselves up to date with developments of both general and subject-specific standards and best practices for research data management. The combination of being trained as both researchers and research data management specialists makes them highly qualified for supporting the data stewardship of their institutional collection within DataverseNO. The responsibility for the management and curation of the institutional collections is placed at the different partner institutions precisely because they know the needs and therefore are best suited to serve the research communities at their institution, and thus, the user groups of the respective institutional collections within DataverseNO.
Data curators are responsible for ensuring that data published in each collection within DataverseNO (including the top-level collection) are curated according to the DataverseNO policies and guidelines, and in line with best practice recommendations and the needs of the different user communities at stake (see R0 on partner agreements and Designated Community). Curators communicate with the different user communities represented in the collection(s) they curate, e.g. during curation, but also through other channels and in other venues. Curators also communicate with the management of their collection, and with curators of other collections within DataverseNO building the DataverseNO Network of Expertise. This network of curators covers the different aspects of data curation, including metadata, file formats, and licensing. In addition to enabling knowledge and experience exchange, this network also makes sure that curation practices across the repository are aligned with the DataverseNO policies and guidelines, and also seeks to align curation practices across institutional collections from different partner institutions containing data from the same or similar scholarly disciplines. At collection launch, each partner institution starts off with at least two curators. UiT has currently eight curators. See also discussion about resource scaling in section II Funding below.
DataverseNO is organized in a way that ensures sufficient funding for the operation and further development of the repository in a long-term perspective.
To be noted on a general level, both the owner institution and the partner institutions are state-owned universities and thus part of the national, governmental higher education and research system and under the ultimate responsibility of the Norwegian Ministry of Education and Research . They are all reputable institutions that have existed for many decades – though in some cases not under their current name. Thus, they all are organized and funded in a way that ensures the operation of sustainable services for higher education and research in an enduring perspective. Also, all institutions involved in DataverseNO have recognized Open Science as an important issue in their missions.
Still on a general level, it is also of utmost importance to make clear that – as is the case for any other sustainable service – both the owner institution and the partner institutions of DataverseNO allocate their funding and resources to the operation and development of DataverseNO on a scalable basis, but always to a sufficient extent in order to completely fulfill their commitments at any time. This means, e.g., that a partner institution does not allocate all their research support staff to the operation of their institutional collection within DataverseNO right from the establishment of the collection. Allocation of resources on a scalable basis means that necessary funding and staff are allocated gradually as data deposit into the collection increases. This scalable model has proved to be very successful and sustainable in the development and operation of similar services at higher education and research institutions in Norway.
Furthermore, although the resources needed e.g. for data curation increase as more researchers at DataverseNO partner institutions choose to deposit their data into DataverseNO, we expect, and have already experienced, that the average time used on data curation per dataset will decrease as researchers become more proficient in research data management the more datasets they have deposited into the repository and the more research data management training they have received at the partner institution or elsewhere. The details presented below should be understood on this general background.
Owner of DataverseNO
UiT The Arctic University (owner of DataverseNO) has a long-standing record as a pioneer in promoting Open Access, Open Data and Open Science in Norway, and has as a goal in its present strategy (2018-2022) to be nationally leading in Open Science . Thus, there is a strong commitment at the institution to long-term support, strategic priority and sustainable funding of activities and services like DataverseNO, for the benefit of the institution. In particular, as described in the official and publicly available Steering Document for DataverseNO , UiT commits to the partner institutions and the Designated Community of DataverseNO to ensure the proper management and operation of DataverseNO in a long-term perspective, and in accordance with the responsibilities described in this document.
By signing the partner agreement, the partner institutions of DataverseNO commit to operate their institutional collections according to DataverseNO policies and guidelines. Although not explicitly mentioned in the agreement this implies that they have to ensure sufficient funding and resources as well as sufficiently qualified staff to fulfill these requirements at any time.
Funding model of DataverseNO
Before DataverseNO was established as a national generic repository for open research data, the repository served as a generic institutional repository for UiT The Arctic University of Norway, operated and funded by the institution. As the founder and owner of DataverseNO and due to the institutional need for such a service, UiT The Arctic University of Norway takes the responsibility for the basic funding of the repository. The partner membership fees cover UiTs overhead expenses for offering DataverseNO to their partner institutions. These overhead expenses are related to the management, the operation, and the development of the repository, but not to data curation of any sort – since data curation is the responsibility of the partner institutions. Each partner institution covers their expenses for necessary staff resources, competence building and attending meetings, etc.
Allocation of staff
Currently (as of February 2020), the following staff resources are allocated to the operation and further development of DataverseNO. See discussion of scalable model above.
Repository Management and Operation
- Three permanent staff members from the UiT Library responsible for service management; approx. 2 FTEs
- Four permanent staff members from the UiT Library and the UiT IT department for technical operation and maintenance of the repository; approx. 0.75 FTEs
- One permanent staff member from the Research administration at UiT for alignment with UiT strategy; approx. 0.1 FTEs
- One permanent staff member from the IT department at UiT for strategic development of IT infrastructure; approx. 0.1 FTEs
Collection Management and Operation
- Two permanent staff members for collection management at each of the following seven partner institutions: Inland Norway University of Applied Sciences, Nord University, Norwegian University of Life Sciences, University of Agder, University of Stavanger, University of Bergen, Western Norway University of Applied Sciences
- Three permanent staff members for collection management at each of the following two partner institutions: NTNU - Norwegian University of Science and Technology, UiT The Arctic University of Norway
As is apparent from the overview (see section I Organization above) of deposited and published datasets in the different institutional collections, apart from UiT, all collections are still in their establishing phase. The number of FTEs for the management of these collections are currently approx. 0.2 for each collection. At UiT the corresponding number is approx. 0.5 FTEs.
TROLLing has two permanent staff members for collection management. The current allocation of FTEs for the management of TROLLing is approx. 0.3 FTEs.
- At least two permanent staff members for data curation of each institutional collection of DataverseNO. Institutions with more staff members: Nord (3), UiB (3), NTNU (4), UiA (4).
- Eight permanent staff members for data curation of the institutional collection for UiT and the DataverseNO top-level collection
- Two permanent staff members for data curation of TROLLing
The current allocation of FTEs for the management of these collections are as follows:
- HVL Open Research Data: approx. 0.1 FTEs
- INN Open Research Data: approx. 0.1 FTEs
- NMBU Open Research Data: approx. 0.3 FTEs
- NORD Open Research Data: approx. 0.1 FTEs
- NTNU Open Research Data: approx. 0.4 FTEs
- UiA Open Research Data: approx. 0.3 FTEs
- UiB Open Research Data: approx. 0.3 FTEs
- UiS Open Research Data: approx.. 0.1 FTEs
- UiT Open Research Data (incl. special collection (TROLLing), and top-level collection): approx. 4 FTEs
To summarize, the staff resource allocated to the operation and development of DataverseNO amounts to a total of approx. 52 permanent staff members accounting for approx. 11 FTEs. (Note that in quite a few cases a single staff member may have different roles in DataverseNO; the total number of staff members reported above applies to unique staff members.)
In addition to the commitment described above, each partner institution (incl. UiT) allocates an increasing amount of staff resources to provide research data management training for research support staff, researchers, and students at the institution (see section III below). Although these resources are not included in the numbers above, they undoubtedly benefit the operation of DataverseNO as they – among other things – contribute to increase the pool of qualified Research Data Service staff who may be allocated to the operation and curation of institutional and special collections within DataverseNO.
III. Training and Professional Development
All management, operation, data curation, and development of DataverseNO are carried out by permanent research support staff members at the DataverseNO owner institution and the DataverseNO partner institutions. As explained above, these institutions are all higher education and research institutions in Norway. As such, they place great emphasis on ongoing training and professional development of their employees as part of their ordinary work tasks. The Research Data Service staff involved in the operation of DataverseNO keep themselves up to date on developments within the scholarly disciplines they provide research support services for, as well as on standards and best practice recommendations for research data stewardship. They regularly attend workshops, webinars, training courses, conferences, and other training events on research data stewardship, both in Norway and abroad. Among the conferences and training events attended in the past five years are the annual meeting of the International Association of Social Science Information Services and Technology (IASSIST), the plenary meetings of the Research Data Alliance (RDA), Dataverse Community Meetings, the International Data Curation Conference (IDCC), in addition to several national and Nordic events, e.g. workshops on ethical issues in research data management organized by NSD - Norwegian Centre for Research Data. Recently, two members of the Research Data Staff at UiT The Arctic University of Norway received a GO FAIR Readiness Certificate after attending a 4-day course on FAIR data stewardship .
In addition to the training activities mentioned above, UiT The Arctic University of Norway – as the owner of DataverseNO – take special responsibility for keeping the repository and the involved personnel up to date with any matters relevant to the proper operation of the repository in accordance with international standards and best practice recommendations. UiT offers regular training courses on how to manage research data, including training in how to archive and share research data. The courses are run by Research Data Service staff from the Library (main contributor), the IT department, and the Research administration at UiT. The courses cover all levels from basic research data management to different advanced topics . The contents of these training activities as well as the competence and the experiences from these activities are shared with the partner institutions of DataverseNO. Also, UiT and/or its personnel are members and actively participate in international bodies including CLARIN, Liber, and RDA (see also R6).
Expertise in data curation and other aspects of data stewardship relevant to the proper operation of DataverseNO is shared through different channels within DataverseNO, e.g. via the DataverseNO Advisory Committee, and the Network of Expertise established between the data curators of the different collections within DataverseNO. Furthermore, the newly established national RDA group for Norway will play an essential role in the training of Research Data Service staff at higher education and research institutions in Norway, and also in the alignment of practices for research data management in Norway with international standards and best practice recommendations . One of the repository managers of DataverseNO and one of the managers of the institutional collection of NTNU are involved as key personnel of the Norwegian RDA group, and we expect the activities and outcomes of the group to be of great benefit for DataverseNO.
IV. Range and Depth of Expertise
The owner institution as well as the partner institutions of DataverseNO have as their main mission to provide high-quality services in the higher education and research sector, and they have done so for many decades. The research support staff at these institutions have high-level and in-depth expertise on the different scholarly subjects for which they offer services. The Research Data Service staff responsible for the operation and development of the DataverseNO repository and its collections consist of a range of individuals who are highly qualified for their tasks.
The repository and collection management is carried out by permanent library staff members with at least graduate education in addition to training in research data stewardship. They have long experience from developing and operating research support services, e.g. Open Access publishing services. The technical aspects of the repository are taken care of by computer engineers with graduate education and long experience from developing, operating, and maintaining the technical infrastructure of research support services.
Data curation in DataverseNO is carried out by permanent library staff members at the owner institution and at the partner institutions. Most of these staff members are (Senior) Research Librarians, many of which with PhD (level) education within the scholarly subjects they curate research data from. In addition, they have been – and are continuously – trained in standards and best practices for research data management. The DataverseNO curators also share and align their expertise and practice through the DataverseNO Network of Expertise.
Although the mission of DataverseNO – with the possible exception of special collections – is to be a national GENERIC repository for open research data, the repository strives to provide subject-specific expertise as far as possible; see R6, R8, and R11. This is why, as a main rule, data deposited into institutional collections or into the top-level collection of DataverseNO are curated by Research Data Service staff who are subject specialists in addition to being trained in research data management. Special collections of DataverseNO are without exception managed and curated by permanent Research Data Service staff who are subject specialists.
 Organization of DataverseNO: https://site.uit.no/dataverseno/about/#organization-of-dataverseno
 DataverseNO Steering Documents: https://site.uit.no/dataverseno/about/steering-documents/
 DataverseNO Policy Framework: https://site.uit.no/dataverseno/about/policy-framework/
 DataverseNO Administrator Guidelines:
 DataverseNO Curator Guidelines: https://site.uit.no/dataverseno/admin-en/curatorguide/
 DataverseNO Deposit Guidelines: https://site.uit.no/dataverseno/deposit/
 DataverseNO support page: https://site.uit.no/dataverseno/support/
 TROLLing Scientific Advisory Board: https://site.uit.no/trolling/people/
 State-owned universities and university colleges in Norway: https://www.regjeringen.no/en/dep/kd/organisation/kunnskapsdepartementets-etater-og-virksomheter/Subordinate-agencies-2/state-run-universities-and-university-co/id434505/
 Strategic plan for UiT The Arctic University of Norway 2014-2022:
 FAIR data stewardship course: https://indico.neic.no/event/56/
 Research data management training @ UiT: http://site.uit.no/rdmtraining/?lang=en
 RDA Group Norway: https://rd-alliance.org/groups/rda-norway