Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)

Figures & Tables

Template that inspired the creation of FAIRIST.

FAIR DIMENSION
Findable	Data will be assigned a PID <how?> and will be referenced on the <project website> A catalog entry will be added to <FAIR Data Point or community/institutional catalog>. Metadata and links to related ontologies will be available on the <project website>. Where tags exist, schema.org descriptors will be utilized.
Accessible	Available via <storage location>, that doesn’t require specialized software to access. This includes both the raw data and curated or derived data. The surrogate and other ML benchmarks will be deposited in <repository>. Any APIs will be versioned and described, linked from the <project website>.
Interoperable	Code stored on github and linked from the <project website> Uses libraries from <project name> that utilize <standard or standard Python libraries, etc.>. Uses standard references for <more here>. Both input and output data are in <specify> format.
Reusable	ML model and data will be deposited at <repository>. Notebooks will demonstrate how to assemble model and sample training datasets. Each notebook product will be assigned a DOI using <specify DOI source>. The <project> notebook interface is on <place shared, e.g., github>. Provenance of the simulation creation will be available as part of the metadata. A designation will be added to the website noting that all data as licensed under Creative Commons Attribution 4.0 International License.

Example Output from FAIRIST Showing Recommendations.

FAIRIST Recommendations Based on your responses, the following recommendations are included for your consideration and/or inclusion in your project’s Data Management Plan.
Types of Data Research objects associated with the project can be classified into the following groups: Data (Machine Learning) Models
Data Stewardship Practices Planned Table 1 shows specific data stewardship actions that will be undertaken during the project as they relate to the high-level goals of FAIR.
FAIR DIMENSION	RESEARCH DATA STEWARDSHIP PRACTICES PLANNED
Findable	Research products will be posted to the Project website. Data will be assigned a unique identifier per community best practices and will be referenced on the Project’s website. Metadata and links to related ontologies will be available on the Project website. Where tags exist, schema.org descriptors will be utilized.
Accessible	Available via open, web accessible folder. All data is open.
Interoperable	Code stored on github (and linked from the Project website). Uses libraries included with the code. Both input and output data are in HDF5 format.
Reusable	ML model and data will be deposited at OpenML.org. A notice posted will designate research objects as licensed under CC-BY.
Table 1: Data Stewardship Practices Planned by FAIR Dimension