AbstractMost research intensive institutions provide some form of data management support. However, the form in which these services are offered and how extensive these are differ and are often difficult to compare. Objective comparison of the different types of services is needed to evaluate the effectiveness of the diverse approaches and to make informed decisions about their usefulness. In this practice paper, we discuss a collaborative effort between Delft University of Technology (TU Delft), École Polytechnique Fédérale de Lausanne (EPFL), University of Cambridge and University of Illinois, which resulted in the development of a short survey to assist institutions in increasing the effectiveness of their data management support services and their evolution. Different approaches to a common goal Informal discussions between the research data service teams of TU Delft, EPFL, University of Cambridge and University of Illinois revealed that each institution had undertaken a different approach in designing their data support services. TU Delft has a central research data support team at the Library1, which is also part of a consortium of four Dutch technical universities (4TU)2. In addition, TU Delft is embarking on a Data Stewardship project, which will provide disciplinary support for data management embedded at faculties (Teperek et al., “Data Stewardship – addressing disciplinary data management needs”, abstract submitted to IDCC18). EPFL has a central data management support team, which provides generic, as well as on-demand, tailored training and data consultations to the research community3. This team is also assisted by liaison librarians, who know the data management needs of their faculties and help the central support to shape their service to meet disciplinary requirements. EPFL is also an active player in the national Digital Lifecycle Management project4. The University of Cambridge, in addition to small central team supporting researchers in data management, also has a dedicated programme of Data Champions - researchers volunteering their time to advocate for good data management in their local communities5. The University of Illinois has a central data management support team and is also part of a national network of subject-specific data curators6. Despite these differences, the goal of the four service providers is the same: to improve data management practice within their research communities. How can we therefore compare how good our approaches are towards achieving our common goal? Evaluation of existing measures Members of the four institutions first reviewed existing tools to assess data management support services. We first looked at the Research Infrastructure Self Evaluation Framework (RISE) framework survey created by the Digital Curation Centre7. However, we thought that this framework was more suitable for assessing the maturity of the data services offered. We then looked at the Data Asset Framework (DAF) used by several UK institutions8. The DAF survey is a comprehensive tool that allows institutions to assess researchers’ data management practice and identify gaps in service provisions; thus in principle, it should meet our requirements. However, the DAF survey consists of over sixty questions, which was not compatible with the repeated assessment we plan to do. We therefore decided to follow its general principle, but do something simpler and less resource-intensive. Short survey on data management practice Based on the DAF survey, we came up with a list of ten multiple choice questions that we found essential to reflect on researchers’ data management practice. By limiting the number of questions to ten and by ensuring these were multiple choice, we thought that first we were respectful of researchers’ time, and secondly, the approach would allow for results standardisation and comparison. In addition to a commonly agreed set of questions, each institution was able to add their own specific questions to obtain more granular information about the different research units and to get feedback about specific services provided to their research communities. Anticipated outcomes TU Delft and EPFL will launch the survey in October 2017, and will be followed by the University of Cambridge and the University of Illinois. We anticipate that the first comparative results will be available at the beginning of 2018. We expect that the results of the survey will provide a useful initial assessment of current data management practices across research communities, which will highlight to institutions where biggest gaps are and where more work is needed. The results will help understand the different disciplinary needs and the maturity of subject-specific data management practice, thus, allowing a more targeted approach. In addition, comparing the results between the institutions will hopefully highlight strengths and weaknesses of the different approaches they took in developing their data management support and will hopefully lead to best practice exchange. Limitations As with any other methodology based on surveys, there are limitations to our approach, which will affect the type of conclusions that can be drawn. First, the respondents will be self-selected, and therefore may not be representative of the research communities we are trying to sample. Secondly, institutions need to be cautious interpreting potentially different results for diverse groups of respondents as these might not be directly related to the quality or availability of data support services and might be affected by external factors, such as community norms, specific funders’ policies, influence of local authorities etc. Finally, the limited number of questions used in the survey limits the depth of possible conclusions about data management practices.Nonetheless, we believe that the benefits of our lightweight data management practice assessment, make the approach worth testing. Next steps The initial results, expected in early 2018, will allow us to evaluate whether the survey allows for comparative assessment of data management practice. If the survey proves to be suitable for such measurements, we will continue to use it to regularly evaluate the maturity of researchers’ data management practice at our respective institutions. Additionally, we plan to share the survey under a CC BY licence to enable others to use the tool for their assessments and to allow comparisons and collaborations with other institutions. References 1. Research Data Management. TU Delft Available at: https://www.tudelft.nl/library/themaportalen/research-data-management/. (Accessed: 19th October 2017) 2. 4TU.ResearchData: Home. Available at: http://researchdata.4tu.nl/home/. (Accessed: 19th October 2017) 3. ResearchData | EPFL. Available at: https://researchdata.epfl.ch/. (Accessed: 19th October 2017) 4. Home :: DLCM. Available at: https://www.dlcm.ch/. (Accessed: 19th October 2017) 5. Higman, R., Teperek, M. & Kingsley, D. Creating a Community of Data Champions. bioRxiv 104661 (2017). doi:10.1101/104661 6. Johnston, L. R. et al. Data Curation Network: A Cross-Institutional Staffing Model for Curating Research Data. (2017). 7. RISE, a self-start tool for research data management service review | Digital Curation Centre. Available at: http://www.dcc.ac.uk/news/rise-self-start-tool-research-data-management-service-review. (Accessed: 15th October 2017) 8. Rob Johnson, Tom Parsons & Andrea Chiarelli. Jisc Data Asset Framework Toolkit 2016. (Zenodo, 2016). doi:10.5281/zenodo.177876
Plan d'action pour le site DLCMDeadline for new website : end of July 2017 Contact : Bineta Ndaye, UNIGE (email@example.com) General DesignPlease check Branding Guidelines of DLCMPay attention to contrast (which currently is very bad)Search functionalitiesfiltersMenuMenu on top: Home, Project, Services, Partners, Contact For inspiration, take a look at : http://dhlab.unibas.ch/activity/ Content of menu tabsHome What is DLCM? Add data life-cycle in the style of : http://www.data-archive.ac.uk/create-manage/life-cycle Key Resources and services available from DLCMUpcoming Events (upcoming trainings will be integrated here as well) : https://www.dlcm.ch/events/category/events/News : https://www.dlcm.ch/category/news/Project Project Organization https://www.dlcm.ch/about-us/project-organization/UpdatesServices Every service as tile as in : https://www.vigiswiss.ch/fr/data-center/Services to be promoted so far:DMP DLCM ChecklistDLCM TemplateTo learn more (other resources)PolicyDLCM TemplateTo learn more (other resources)Tools Collection (?) or a few assorted tools, which we support? Coordination DeskELN ServiceLabkeysLIMSopenBISTo learn more (other resources)Long-Term PreservationCost Model avec estimation dateTo learn more (other resources)Expert NetworkDLCM Expert Map DLCM Consulting https://www.dlcm.ch/consulting/ Partnersall project partners, to be found here : https://www.dlcm.ch/about-us/partners/ SwitchEngineSDSCOther? ContactGood idea: https://www.favre-guth.ch/a-propos/teamAnother good idea: http://dhlab.unibas.ch/team/Names and generic contacts of all responsibles of each track At the moment, not all have photos, that's why, the name and contact is enough
_First brainstorm_ AUDE DIEUDÉ, ANA SESARTIC, PIERRE-YVES BURGI, ELIANE BLUMER WHAT WE ACTUALLY WANTED TO DO... With this background, this workshop aims at providing the unique opportunity to share the insights, experiences and best practices regarding innovative practices regarding long-term preservation of research data. This Swiss DLCM project, with its experience gained from concrete implementations, and which involves at the various partner institutions research units, IT services, and libraries – will serve as springboard for promoting and animating the discussion and debate across countries and continents. The audience for this workshop will target large communities of researchers nationally and internationally. HERE, SOME FIRST IDEAS FROM MY SIDE... We have in total 2x90min = 180min 1. Make an interactive exercise directly at the beginning by asking them about their experiences in RDM (30min) - Introduction round, where everyone tells their background & motivation for attending the workshop. - “placemat method” (was used in our training course) proved to be an effective way to gather one’s RDM experiences (see https://de.wikipedia.org/wiki/Placemat_Activity and http://www.humber.ca/centreforteachingandlearning/instructional-strategies/teaching-methods/classroom-strategies-designing-instruction/activities-and-games/place-mat.html) - (if you need ideas for icebreaker activities, http://www.icebreakers.ws/ has a good overview) 2. Give a short overview of what has happened in DLCM for all the points above (30min) - Insights - Experiences - Best Practices - Concrete Implementations 3. Split into smaller groups (if we have enough participants), give them our concrete implementations (see below) and let them discuss/compare it to other existing examples (if necessary share other examples, if they do not have any on their own (45min) - specifications - Active Data Research Management (ADRM) - checklist - policy 4. Make a plenum/discussion (45min) TO DO - What material do we need to prepare? - Marketing material (which one? from which institutions?) - Will we give handouts to the people, summarizing what’s been done at DLCM? Including contacts & pointer to website...? - Flipcharts and the like will be available on the premises, I assume?