Data discovery

[pietercolpaert]

Challenge Description

When

• starting a new project, or
• moving an existing project into another domain, or
• maintaining your project for a long period of time,

you somehow need to find interoperable, relevant and trustworthy datasets. Today, this is a manual task. Automating this task requires a discovery mechanism, which on the Web today is an unsolved problem.

Example cases:

1. Setting up a new route planner.
2. Moving digital twin software from one city to another.
3. Creating a dashboard of a certain indicator, adding more data when it becomes available.

Impact and Importance

Automating data discovery should reduce the costs for:

1. setting up a new project
2. bringing the project into another context
3. maintaining the project over time

Desired Solution

1. A language to express the criteria for a dataset to enter your project, based on: the shape or schema used (e.g., SHACL), the provenance (e.g., only datasets that originate from X or Y), geo-temporal extent, usage conditions, etc.
2. A data model for Web-based storage system or data catalog so that the criteria can be evaluated.
3. An algorithm to evaluate 1 over 2

Acceptance Criteria

1. A specification is available of the language with examples on how to express datasets relevant to your application
2. A data model specification is available
3. A reference implementation of the algorithm can be tested

References and Resources

• Describing a data catalogs and their datasets with e.g., geotemporal aspects: DCAT
• Describing policies: ODRL
• For pipelines and provenance, see Pipelining workflows across participants #1

[TallTed]

SeeAlso: Describing Linked Datasets with the VoID Vocabulary