Ten principles for machine-actionable data management plans

Abstract

Data management plans (DMPs) are documents accompanying research proposals and project outputs. DMPs are created as free-form text and describe the data and tools employed in scientific investigations. They are often seen as an administrative exercise and not as an integral part of research practice. There is now widespread recognition that the DMP can have more thematic, machine-actionable richness with added value for all stakeholders: researchers, funders, repository managers, research administrators, data librarians, and others. The research community is moving toward a shared goal of making DMPs machine-actionable to improve the experience for all involved by exchanging information across research tools and systems and embedding DMPs in existing workflows. This will enable parts of the DMP to be automatically generated and shared, thus reducing administrative burdens and improving the quality of information within a DMP. This paper presents 10 principles to put machine-actionable DMPs (maDMPs) into practice and realize their benefits. The principles contain specific actions that various stakeholders are already undertaking or should undertake in order to work together across research communities to achieve the larger aims of the principles themselves. We describe existing initiatives to highlight how much progress has already been made toward achieving the goals of maDMPs as well as a call to action for those who wish to get involved.

Data Management Plans A Review

“…Miksa et al use the shorthand of describing them as "awareness tools." 16 Plans can include aspects relating to "preservation, documentation, and sharing of data, samples, physical collections, curriculum materials and other related research and education products" 17 and are meant to support sharing. They are distinct from data management planning which is less based on a formal document and more of a process or workflow for managing active research data.…”

“…The literature surveyed in this review finds an overall ambivalence to DMPs on the part of researchers. Miksa, et al categorise DMPs as "an annoying administrative exercise" that is ultimately not supportive of RDM 16 . Research that specifically analyses the DMPs or their use, once completed, tends to find them and the process used to create them, to be largely ineffective.…”

Gestión de datos de investigación y bibliotecas: preservando los nuevos bienes científicos

“…Los PGDs son requeridos por una gran parte de las agencias de financiamiento y cada vez hay más iniciativas para mejorar su legibilidad por máquinas, de forma que los investigadores solo deban completar un mínimo de preguntas y el resto de la información sea recuperada de otras infraestructuras (p.ej. repositorio, bancos de publicaciones o ORCID) (Miksa, Simms, Mietchen y Jones, 2019;Miksa, Rauber, Ganguly y Budroni, 2017).…”

Framing the scope of the common data model for machine-actionable Data Management Plans

“…As is the case for the DMP, there is also a proposal for a set of 10 principles and practices that are specific to the maDMP [13]. These principles and practices were conceived to both aid in the application of the maDMP concept, as well as, to realise its benefits.…”

“…12 TPDL 2018 Website: http://www.tpdl.eu/tpdl2018/ 13 A visual representation of these workflows as BPMN (Business Process Model and Notation) flows can be consulted here: https://goo.gl/72QFwX Fig. 2: GitHub project board used to organise user stories.…”