TY - JOUR
T1 - Policy needs to go hand in hand with practice
T2 - The learning and listening approach to data management
AU - Cruz, Maria
AU - Dintzner, Nicolas
AU - Dunning, Alastair
AU - Kuil, Annemiek van der
AU - Plomp, Esther
AU - Teperek, Marta
AU - Turkyilmaz - van der Velden, Yasemin
AU - Versteeg, Anke
PY - 2019
Y1 - 2019
N2 - In this paper, we explain our strategy for developing research data management policies at TU Delft. Policies can be important drivers for research institutions in the implementation of good data management practices. As Rans and Jones note (Rans and Jones 2013), " Policies provide clarity of purpose and may help in the framing of roles, responsibilities and requisite actions. They also legitimise making the case for investment”. However, policy development often tends to place the researchers in a passive position, while they are the ones managing research data on a daily basis. Therefore, at TU Delft, we have taken an alternative approach: a policy needs to go hand in hand with practice. The policy development was initiated by the Research Data Services at TU Delft Library, but as the process continued, other stakeholders, such as legal and IT departments, got involved. Finally, the faculty-based Data Stewards have played a key role in leading the consultations with the research community that led to the development of the faculty-specific policies. This allows for disciplinary differences to be reflected in the policies and to create a closer connection between policies and day-to-day research practice. Our primary intention was to keep researchers and research practices at the centre of our strategy for data management. We did not want to introduce and mandate requirements before adequate infrastructure and professional support were available to our research community and before our researchers were themselves willing to discuss formalisation of data management practices. This paper describes the key steps taken and the most important decisions made during the development of RDM policies at TU Delft.
AB - In this paper, we explain our strategy for developing research data management policies at TU Delft. Policies can be important drivers for research institutions in the implementation of good data management practices. As Rans and Jones note (Rans and Jones 2013), " Policies provide clarity of purpose and may help in the framing of roles, responsibilities and requisite actions. They also legitimise making the case for investment”. However, policy development often tends to place the researchers in a passive position, while they are the ones managing research data on a daily basis. Therefore, at TU Delft, we have taken an alternative approach: a policy needs to go hand in hand with practice. The policy development was initiated by the Research Data Services at TU Delft Library, but as the process continued, other stakeholders, such as legal and IT departments, got involved. Finally, the faculty-based Data Stewards have played a key role in leading the consultations with the research community that led to the development of the faculty-specific policies. This allows for disciplinary differences to be reflected in the policies and to create a closer connection between policies and day-to-day research practice. Our primary intention was to keep researchers and research practices at the centre of our strategy for data management. We did not want to introduce and mandate requirements before adequate infrastructure and professional support were available to our research community and before our researchers were themselves willing to discuss formalisation of data management practices. This paper describes the key steps taken and the most important decisions made during the development of RDM policies at TU Delft.
KW - Code
KW - Data archive
KW - Data champions
KW - Data repository
KW - Data stewardship
KW - Open science
KW - Policy
KW - Policy development
KW - Policy implementation
KW - RDM
KW - Research data management
KW - TU Delft
UR - http://www.scopus.com/inward/record.url?scp=85073374944&partnerID=8YFLogxK
U2 - 10.5334/dsj-2019-045
DO - 10.5334/dsj-2019-045
M3 - Article
VL - 18
JO - Data Science Journal
JF - Data Science Journal
IS - 1
M1 - 45
ER -