FAIR Principles
Metapages supports, aligns, and hopes to even extend the FAIR principles, with the caveat that metapages are about connecting code and compute to data, with our emphasis on code and compute. So some of these principles are not quite applicable and we [Problem Internal Link].
FAIR principle alignment
A core part of the commitment that users metapage workflows will be able to run forever is the deployment of a standalone metapage viewer that can run and display archived metapages. This viewer is open-source and deployed separately from the main application:
https://github.com/metapages/archive.metapage.io
More information found here
| FAIR Principle | Status | Description |
|---|---|---|
| F1: (Meta) data are assigned globally unique and persistent identifiers | ✅ | Metapages and metaframes get globally unique and persistent unique ids in the URLs. E.g. https://metapage.io/dion/ab59f026e2094069ab4aea83a2c30797. See here for URL structure |
| F2: Data are described with rich metadata | ✅ | Metapage resources include name, description, authors, tags, dates, provenance (which metapage this was cloned from), in a simple JSON format (see this example). The metapage workflow components include similar metadata, and all code and embedded data can be machine inspected. We will add any metadata that we have overlooked that researchers could use. |
| F3: Metadata clearly and explicitly include the identifier of the data they describe | 🏗️ On our roadmap | Although the URL contains the identifier, currently the metadata does not also have it embedded. |
| F4: (Meta)data are registered or indexed in a searchable resource | ✅ | All metadata is indexed immediately and available for search-as-you-type! |
| A1: (Meta)data are retrievable by their identifier using a standardised communication protocol | ✅ | Metapages are workflows that live in the browser, all communication is via over standard HTTPS |
| A1.1: The protocol is open, free and universally implementable | ✅ | See above |
| A1.2: The protocol allows for an authentication and authorisation procedure where necessary | ✅ | Our resources have a layered permissions model, allowing public, private, per user, per group, and sharing, where authentication is then required for non-public resources. |
| A2: Metadata should be accessible even when the data is no longer available | ✅ | We keep metapage definitions around forever if published, which contains the metadata. |
| I1: (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation | ✅ | The resource metadata (metapage JSON definitions) are in a simple JSON format, with descriptions and types in an open source published package |
| I2: (Meta)data use vocabularies that follow the FAIR principles | Not applicable | Metapage metadata currently does not use any vocabularies that require identifiers |
| I3: (Meta)data include qualified references to other (meta)data | ✅ with caveats | This applies to data, however metapages is about code and compute connecting data. We [Problem Internal Link]. For metapage resources, we link to other internal resources and store provenance and history |
| R1: (Meta)data are richly described with a plurality of accurate and relevant attributes | Not applicable | This is strictly about generated or experimental data, which is what metapages operate on, but do not themselves generate. |
| R1.1: (Meta)data are released with a clear and accessible data usage license | 🏗️ On our roadmap | We plan to implement simple and transparent attachments of licenses to user created workflows |
| R1.2: (Meta)data are associated with detailed provenance | ✅ | Copied metapages store the origin metapage, and resources contain the owner, creation date, etc |
| R1.3: (Meta)data meet domain-relevant community standards | 👀 Not yet applicable | There are currently no relevant community standards, we hope to establish one |
The goal of the FAIR principles is to
improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.
The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.
One of the goals of the metapage platform is to make scientific workflows instantly findable, editable, and shareable.
Metapages are well-positioned, as they are machine readable, using JSON to describe their inputs, outputs, metadata, and often the code is directly readable.