Welcome in MetaShARK

DISCLAIMER: some features are still in development. Some parts with this color code are not meant to be fully functional.

MetaShARK

MetaShARK (Metadata Shiny Automated Resources and Knowledge) is a tool designed for ecology data description tasks. The tool relies on ecology metadata standards, and mainly the Ecological Metadata Language. Its vocation is to allow any ecologist to fill in metadata for its dataset to permit the understanding, resusability and reproducibility of his work. But as metadata is becoming more and more complex, this tool is trying to get as user-friendly as possible.

`MetaShARK` is written and maintained by the French National Biodiversity Data Hub (PNDB). You can interact with the development team on their git repository.

EML

The Ecological Metadata Language has been developped since 1997 from the work of Michener et al.. Since then, it has been developped by the NCEAS (National Center for Ecological Analysis and Synthesis) and is mainly accessible through its github repository. However, MetaShARK offers a documentation section dedicated to EML.

MetaCat & MetaShark

The application you are currently using is a front-end tool for any user who wants to contribute to a DataOne node repository, also known as metadata catalog or MetaCat. To contribute to a MetaCat, you need to login to the metacat in which you want to upload your data package. Then, it will be possible for MetaShARK to gather the needed informations, as you will see while using the app.

About EML Assembly Line

Authorship

The `EML Assembly Line` package used in this app and its children is the intellectual property of the Environment Data Initiative (EDI). You can find further details on their git repository.

Usage

EMLassemblyline is a metadata builder for scientists and data managers who need to easily create high quality EML metadata for data publication. It emphasizes auto-extraction of metadata, appends value added content, and accepts user supplied inputs through template files thereby minimizing user effort while maximizing the potential of future data discovery and reuse. EMLassemblyline requires no familiarity with EML, is great for managing 10-100s of data packages, accepts all data formats, and supports complex and fully reproducible science workflows. Furthermore, it incorporates EML best practices, is based on a simple file organization scheme, and is not tied to a specific data repository.

(preface by Colin Smith, EDI)