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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Open scientific data | 10/11 | https://en.wikipedia.org/wiki/Open_scientific_data | reference | science, encyclopedia | 2026-05-05T06:32:28.051815+00:00 | kb-cron |
Research data management can be laid out in a data management plan or DMP. Data management plans were incepted in 1966 for the specific needs of aeronautic and engineering research, which already faced increasingly complex data frictions. These first examples were focused on material issues associated with the access, transfer, and storage of the data: "Until the early 2000s, DMPs were utilised in this manner: in limited fields, for projects of great technical complexity, and for limited mid-study data collection and processing purposes" After 2000, the implementation of extensive research infrastructure and the development of open science changed the scope and the purpose of data management plans. Policy-makers, rather than scientists, have been instrumental in this development: "The first publications to provide general advice and guidance to researchers around the creation of DMPs were published from 2009 following the publications from JISC and the OECD (…) DMP use, we infer, has been imposed onto the research community through external forces" Empirical studies of data practices in research have "highlighted the need for organizations to offer more formal training and assistance in data management to scientists" In a 2017-2018 international survey of 1372 scientist, most requests for help and formalization were associated with data management plan: "creating data management plans (33.3%); training on best practices in data management (31.3%); assistance on creating metadata to describe data or datasets (27.6%)" The expansion of data collection and data analysis processes have increasingly strained a large range of unformal and non-codified data practices. The implication of external shareholders in research projects creates significant potential tensions with the principles of sharing open data. Contributions from commercial actors can especially rely on some form of exclusivity and appropriation of the final research results. In 2022, Pujol Priego, Wareham, and Romasanta created several accommodation strategies to overcome these issues, such as data modularity (with sharing limited to some part of the data) and time delay (with year-long embargoes before the final release of the data).
=== Open science infrastructures ===