Project management: How to sustain and monitor data management in collaborative projects, from practical experience to broader requirementsr

Project management: How to sustain and monitor data management in collaborative projects, from practical experiences to broader requirements Harri Kiiskinen [email protected] Rebase Consulting Data Steward – Module 1 Introduction to Research Data Management and Open Science Tampere University March 21, 20251 1This presentation licensed under CC BY-NC-SA 4.0 Outline Participation of data steward in a research project Data stewarding in during the project life cycle Before the project During the project At the end and after General observations Ideal situation In an ideal situation the data steward is Ipresent in research project planning Ian active participant during the whole research project Ipart of the post-project data cleanup Iconsequently, has good understanding and knowledge of project goals, data sets, methods, and the team Typical situation ILimited data steward resources IPresent for part of the project only ILimited understanding of the project INot able to support the project through its stages Data Management as a service IProvided by the institution IResources allocated from the funding IA pool of data stewards with specialized skillsets IPossible to supplement with external service providers Project life cycle IA project has its life-cycle, starting from the conception of an idea to the publication of the last manuscript ever and the deletion of the last data file. A data steward could (and should) be part of most of these phases. Roles of a data steward and the project life-cycle IBefore project Iplanning stage Ipost-funding / pre-start IDuring project Ibeginning of the project Imid-project Inearing the end IPost-project Pre-project contributions: conception and planning IPlanning of research data management infrastructure IDefinition of required resources IEstimation of costs IOverall definitions of participant roles from data management side IPlanning for data protection issues regarding sensitive data IOverall: feedback and support on the viability of the project idea from the data management perspective. Pre-project contributions: pre-start / post-funding IAllocating DM resources ISetting up source data ingestions processes and practices ISetting up the intermediate and final result data environments IPolicies and practices of intermediate and final result data naming and placement IDefinition of data formats and naming practices for the result data used to support research publications Complications Project ~ funding period IThe project may be longer than a single funding period. IData management while lacking resources Complications Sudden change of project personnel IMultiple causes can for people to leave the project suddenly IConflict of ownership / responsibilities Data stewarding principles IAlways plan for the end-of-project IAim for simple solutions, avoid unnecessary inrfastructure and systems IPrefer plain text formats and open data types IPlan policies and practices that are clear and easy to follow IBe open to in-project changes to data models and infrastructure IYou are the enabler supporting the researchers. Data Management is a service, and we are here to serve. The End Thank you!