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MEx editor

Metadata editor web application.

cookiecutter cve-scan linting open-code

project

The Metadata Exchange (MEx) project is committed to improve the retrieval of RKI research data and projects. How? By focusing on metadata: instead of providing the actual research data directly, the MEx metadata catalog captures descriptive information about research data and activities. On this basis, we want to make the data FAIR1 so that it can be shared with others.

Via MEx, metadata will be made findable, accessible and shareable, as well as available for further research. The goal is to get an overview of what research data is available, understand its context, and know what needs to be considered for subsequent use.

RKI cooperated with D4L data4life gGmbH for a pilot phase where the vision of a FAIR metadata catalog was explored and concepts and prototypes were developed. The partnership has ended with the successful conclusion of the pilot phase.

After an internal launch, the metadata will also be made publicly available and thus be available to external researchers as well as the interested (professional) public to find research data from the RKI.

For further details, please consult our project page.

package

The mex-editor is an angular application that allows creating and editing rules to non-destructively manipulate metadata. This can be used to enrich data with manual input or insert new data from scratch.

license

This package is licensed under the MIT license. All other software components of the MEx project are open-sourced under the same license as well.

development

installation

creating release

  • update version in package.json and CHANGELOG.md
  • commit update git commit --message "..."
  • create a tag git tag ...
  • push git push --follow-tags

commands

  • run npm start to start a local server
  • run npm run lint to lint the project
  • run npm test to start the tests
  • run npm run build to build a package
  • run npm run setup-dummy-data for dummy data

Footnotes

  1. FAIR is referencing the so-called FAIR data principles – guidelines to make data Findable, Accessible, Interoperable and Reusable.