Lead: Mag. Barbara Sanchez Solis (Vienna University of Technology)
More and more funders see data management plans (DMPs) as a prerequisite for the meaningful handling of research data in the funded projects, and some are already working on templates that have to be filled in when submitting projects. At the partner universities, therefore, know-how and expertise in counseling in support of the scientists must be quickly established. Training and consultation documents from the previous project and on-site training by staff from the University of Vienna and the Vienna University of Technology should make this possible. Currently, DMPs are created from Word or PDF templates and are not adapted during the project. The work package Research Lifecycle identifies the stations to which the DMP must be added or adapted in the course of the project. This will turn the DMP into an adjustable document that documents how research data will be handled in the course of the project. So that data repositories and other tools profit from this process, so-called "machine-actionable DMPs" are developed in the project together with DCC and UC3. Information in the DMP, such as the retention period, is then automatically taken into account in connected systems. Finally, it will be evaluated whether a web service developed jointly by DCC and UC3 is also suitable for the central management of DMPs.
Throughout the project, communication with the Austrian funding agencies FWF, FFG and WWTF has been maintained in order to receive regular status updates on open science and DMP and to take these into account in the ongoing work.
The scope of the project included the task of adapting a template to a research discipline in addition to the existing generic template. Employees of The Austrian Social Science Data Archive (AUSSDA) and Vienna University of Econmics and Business implemented this project for the social sciences. They developed a template with a special focus on quantitative data. The initial goal was not to deviate too far from the basic structure of the FWF template, but this was expanded to include the sections "administrative data" and questions about resource requirements.
Heider, Veronika, Raffetseder, Lena, Sanchez Solis, Barbara, & Ulrich, Xenia (2018). DMP Template for the Social Sciences (Version 1.0). Zenodo. DOI 10.5281/zenodo.1291816
The colleagues from the University of Innsbruck made a comparison between the three online tools RDMO, DMPRoadmap and Data Stewardship Wizard. The tools tested use different approaches to creating DMPs. Overall, while the tools are suitable for creating a one-time DMP, they are not interlinkable with existing internal or external systems, do not allow versioning of a "living" DMP, and do not provide centralized rights management.
Haselwanter, Thomas, Miksa, Tomasz & Thöricht, Heike (2019). Comparison of the DMP tools RDMO, DMP Roadmap and Data Steward Wizard. Digital Library of the University Innsbruck. DOI 10.25651/1.2020.0003
The Vienna University of Technology has a proof of concept for an automated DMP tool and will start development soon. The aim is to minimize the manual effort for the researchers while maintaining the quality of the information provided.
The following information is available as docker container on GitHub:
https://github.com/TomMiksa/DMPGenerator
https://github.com/TomMiksa/digital_preservation_ex_1_2
https://github.com/TomMiksa/tu-dpue-lab2-ss18
https://github.com/TomMiksa/DigitalPreservation_2
https://github.com/TomMiksa/digitalpreservation-dmp-generator
https://github.com/TomMiksa/DMPlanner
Examples of landing pages for machine-actionable DMPs:
https://oblassers.github.io/fair-data-science/
https://github.com/oblassers/fair-data-science
The principles of machine-processable DMPs are clearly presented in the article "Ten principles for machine-actionable data management plans" (DOI 10.1371/journal.pcbi.1006750).
Online tools, as they are currently designed, do not add much value beyond our questionnaire-based questionnaire function and awareness building. Future developments should be that they communicate with in-house systems (internal project databases, CRIS systems, address databases, etc.) to truly ensure machine-to-machine actionability. According to the agreement, a DMP tool should not simply be modeled according to the sponsors' specifications, but should be integrated into the workflows of researchers and university systems. However, this is associated with considerable programming work. Therefore, the AG advises data management plans in the final report to invest in the development of automated tools when budgeting for development costs. In any case, as a complement to technical infrastructures, it should continue to support the development of institutional structures for advising on DMPs.