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There are a number of tools for DataCrate in development.
At the University of Technology Sydney, the Provisioner is an open framework for integrating good research data management practices into everyday research workflows. It uses DataCrates as a flexible interchange format to move datasets between diverse research apps such as lab notebooks, code repositories (where data is included by-reference), survey tools, collection management tools, and into archival and publication workflows. Examples of DataCrates moving through the research lifecycle will be provided.
At the University of Technology Sydney, the Provisioner is an open framework for integrating good research data management practices into everyday research workflows. It provides a user-facing research data management planning tool which allows researchers to describe and publish datasets and create and share workspaces in different research apps such as lab notebooks, code repositories (where data is included by-reference), survey tools and collection management tools. DataCrates are used as an interchange format to move data between the different research apps, and as an ingest, archive and publication format. Lightweight adaptors coded against each research app's native API allow export and import of DataCrates, which are then used to move data from one app to another, while recording a provenance history in the DataCrates' metadata. Examples of DataCrates moving through the research lifecycle will be provided.
HIEv DataCrate - At the Hawkesbury Institute for the Environment at Western Sydney University, HIEV harvests a wide range of environmental data (and associated file level metadata) from both automated sensor networks and analysed datasets generated by researchers. Leveraging built-in APIs within the HIEv a new packaging function has been developed, allowing for selected datasets to be identified and packaged in the DataCrate standard, complete with metadata automatically exported from the HIEv metadata holdings into the JSON-LD format. Going forward this will allow datasets within HIEv to be published regularly and in an automated fashion, in a format that will increase their potential for reuse.
