Supporting the use of data: From data repositories to service discovery
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The document discusses supporting the use of data through repositories and service discovery. It provides the example of the MK Data Hub, which allows users to find, share, develop, and get data as well as create applications. Ongoing work involves developing ontological representations of data characteristics like exploitability and applicability, as well as policies and rights. Service discovery requires adequate representation of both available data services and data, including licensing and policy aspects.
Supporting the use of data: From data repositories to service discovery
- 1. Supporting the use of data: From data repositories to service discovery Mathieu d’Aquin Knowledge Media Institute, The Open University mathieu.daquin@open.ac.uk, @mdaquin
- 2. Data repositories are becoming more and more important In education In general For Smart Cities
- 3. The Key Question is: How do we support the exploitation of those data
- 4. ExamplE: The MK Data Hub MK Data Hub Analytics Integration Curation Storage Import Sensor Data Local Stats Gov. Open Data ... Mobile Apps Dashboards Business Intelligence Social Web Apps ...
- 5. Example: The MK Data Hub MK Data Hub Analytics Integration Curation Storage Import Find Share Develop GetCreate
- 8. From A Data Platform to an Experiment Platform
- 9. From A Data Platform to an Experiment Platform
- 10. From A Data Platform to an Experiment Platform Data Services Available Data Ontological representation of service capability Ontological representation of data characteristics Exploitability Applicability
- 11. Ongoing work on Applicability … … … …
- 12. Ongoing work on Exploitability Ontological representation of data characteristics Exploitability Characteristics of the data that needs to be taken into account for exploitability: - Validity, quality, coverage - Nature (time series, statistics, geo, etc) - Scale - Connection, complementarity to others, uniqueness - Policies and rights
- 13. Data Rights and Policies in Data Flows Daga et al (2015), Propagation of policies in rich data flows Given a data flow (the application of data services), how do the licence statements propagate across the data flows? Dataflow representation Input Data licence representation Policy propagation rules Output Data licence representation
- 15. Data Rights and Policies in Data Flows Daga et al (2015), Propagation of policies in rich data flows Given a data flow (the application of data services), how do the licence statements propagate across the data flows? Dataflow representation Input Data licence representation Policy propagation rules Output Data licence representation
- 16. Representation of DatAflows Many options for the representation of workflows (including ProvO) to represent what processes are applied to data. DataNode ontology to represent what in which way these processes actually affect data: Representation of relationships between the data artefact in input and output of the processes.
- 17. Conclusion Service discovery requires not only an adequate representation of the data services (which is not solved) but also the adequate representation of the available data. Including right, policy and licence aspects...
- 19. Need to manage data in more thoroughly