Nature publishes U of I professor’s correspondence on open data

Discipline-specific data and metadata standards should grow from their corresponding scientific communities to ensure relevance to modern scientific research and vitality in real-world applications. Xiaogang (Marshall) Ma, a computer science associate professor at University of Idaho, led an investigation through the Committee on Data (CODATA) of the International Science Council (ISC) in summer of 2022 to discover the status of open data efforts across scientific unions of various disciplines. The result shows a worrying situation. Among 41 ISC member unions and associations, only 25 have sub-organizations dedicated to open data, and just a few have developed machine-readable standards. Recently, the result of the investigation was published as a correspondence [1] to the Nature journal.

To leverage benefits of open data, discipline-specific standards are necessary for FAIR (findable, accessible, interoperable, and reusable) data exchange increasingly by machines. Facing the ever-increasing needs and movements on open data and open science, machine-readable data and metadata standards will be the essential building blocks to support the virtuous cycle of data collection, sharing, discovery, access, and reuse within any scientific communities and beyond to cross-disciplinary areas such as health, humanities and social sciences. In 2017, CODATA set up a Task Group for “Coordinating Data Standards amongst Scientific Unions”, led by Prof. Ma as chair. The group investigated the websites of all the 41 member unions and associations of ISC in 2018, and found that 22 have committees or working groups for data standards and/or data science initiatives. Now, four years after, the result of the 2022 investigation shows that only 3 other unions or associations have taken new actions. Whilst it is possible that many discipline-specific data and metadata standard initiatives might not be listed on their corresponding union websites or may be developed in scientific societies/associations not affiliated with the ISC, in the correspondence Prof. Ma and his co-authors suggested that the scientific unions and associations in any discipline should be aware of the open data and open science movements relevant to their discipline. To fully harness the data revolution, they must take actions to coordinate and facilitate the required standards to make data FAIR and accessible to both humans and machines.