Evolvable DMPs

Vojtěch Knaisl researches evolvability of DMPs and is successfully concluding his PhD research with newly published article Machine-Actionability and Evolvability in Data Stewardship Planning: Framework, Implementation, and Case Study. The paper presents a comprehensive framework for assessing and enhancing the machine-actionability and evolvability of Data Management Plans (DMPs). The research includes the development of a novel implementation that allows for the dynamic adaptation of DMPs in response to changing requirements and conditions. A case study is also provided to demonstrate the practical application of the framework, showcasing how it can be used to improve the management and stewardship of data in various research contexts. This work contributes to the field of data science by providing valuable insights and tools for ensuring that DMPs remain effective and adaptable over time, ultimately supporting better data management practices in research.