_metadata.yml

title: Towards an open-source model for data and metadata standards
authors:
  - name: Ariel Rokem
    affiliations:
      - name: University of Washington
        id: 1
        department: Department of Psychology
        city: Seattle
        state: WA
        country: USA
      - name: University of Washington
        id: 5
        department: eScience Institute
        city: Seattle
        state: WA
        country: USA
    roles: writing
    corresponding: true
    email: arokem@uw.edu
    orcid: 0000-0003-0679-1985
# Add your name and metadata here:
  - name: Vani Mandava
    affiliations:
      - name: University of Washington
        id: 2
        department: Scientific Software Engineering Center
        city: Seattle
        state: WA
        country: USA
      - name: University of Washington
        id: 5
        department: eScience Institute
        city: Seattle
        state: WA
        country: USA
    roles: writing
    orcid: 0000-0003-3592-9453
  - name: Nicoleta Cristea
    affiliations:
      - name: University of Washington
        id: 3
        department: Department of Civil and Environmental Engineering
        city: Seattle
        state: WA
        country: USA
      - name: University of Washington
        id: 5
        department: eScience Institute
        city: Seattle
        state: WA
        country: USA

    roles: writing
    orcid: 0000-0002-9091-0280
  - name: Anshul Tambay
    affiliations:
      - name: University of Washington
        id: 2
        department: Scientific Software Engineering Center
        city: Seattle
        state: WA
        country: USA
      - name: University of Washington
        id: 5
        department: eScience Institute
        city: Seattle
        state: WA
        country: USA
    roles: writing
    orcid: 0009-0004-9010-1223
  - name: Andrew J. Connolly
    affiliations:
      - name: University of Washington
        id: 4
        department: Department of Astronomy
        city: Seattle
        state: WA
        country: USA
      - name: University of Washington
        id: 5
        department: eScience Institute
        city: Seattle
        state: WA
        country: USA
    roles: writing
    orcid: 0000-0001-5576-8189

abstract: |
  Progress in machine learning and artificial intelligence promises to advance research and understanding across a wide range of fields and activities. In tandem, increased awareness of the importance of open data for reproducibility and scientific transparency is making inroads in fields that have not traditionally produced large publicly available datasets. Data sharing requirements from publishers and funders, as well as from other stakeholders, have also created pressure to make datasets with research and/or public interest value available through digital repositories. However, to make the best use of existing data, and facilitate the creation of useful future datasets, robust, interoperable and usable standards need to evolve and adapt over time. The open-source development model provides significant potential benefits to the process of standard creation and adaptation. In particular, data and meta-data standards can use long-standing technical and socio-technical processes that have been key to managing the development of software, and which allow incorporating broad community input into the formulation of these standards. On the other hand, open-source models carry unique risks that need to be considered. This report surveys existing open-source standards development, addressing these benefits and risks. It outlines recommendations for standards developers, funders and other stakeholders on the path to robust, interoperable and usable open-source data and metadata standards.

bibliography: references.bib