Description
The data space approach aims at creating a data federation environment without the overhead of “enterprise” data integration.
The concept of data spaces is gaining more and more importance, as it this approach offers an opportunity for different stakeholders (data owners, including public bodies and municipalities, service providers offering AI-as-a-service algorithms , service consumers, regulatory bodies, etc.) to collaborate. There are several domains from industry via eHealth to education where this kind of data/service federation is expected to have an important role in the near future.
Blockchain, and Hyperledger Fabric in particular, is a natural candidate to support several aspects and steps of such collaborations. However, current initiatives do not really seem to fully exploit the possibilities of HFL (and its support for designing privacy-preserving applications with channels and Private Data Collection).
The Eclipse Dataspace Connector, maintained by a coalition of European organizations, implements the International Dataspace Standard and also serves as a focal point of the Gaia-X. It is designed to connect multi-cloud environments and has an extension mechanism towards different cloud storage technologies. However, currently these extensions only support storage over designated cloud-based services, but do not offer consortial blockchain connection.
The aim of the mentorship would be to develop an extension which support storing data over Hyperledger Fabric as data pane, relying on the Private Data Collection (PDC) mechanism.
Additional Information
Eclipse Dataspace Components project
https://projects.eclipse.org/projects/technology.edc
Extensions as EDC Connectors:
https://github.com/eclipse-edc/Connector/tree/main/extensions
Overall concept of dataspaces:
Reference Architectural Model for Dataspaces https://github.com/International-Data-Spaces-Association/IDS-RAM_4_0
Learning Objectives
The mentee will
- Learn the basic concepts of dataspaces and data connectors
- Gain experience in OS development both for the Hyperledger and Eclipse community.
- Develop chaincode and create basic data model with privacy considerations (using PDC)
- Develop an extension to support the use of HFL as data storage with privacy and resilience guarantees
- Create a documentation which helps the potential (mostly industry-oriented) user community to evaluate the solution
Expected Outcome
- Eclipse Dataspaces Component Connector extension for Hyperledger Fabric (EDC-HFL): specification and basic test cases defined
- EDC-HFL implementation according to the interfaces and structure required by EDC.
- Sample chaincode which serves as a basic EDC conform datastore
- Sample project with typical data sharing scenarios presented
- Documentation and tutorial to facilitate the usage of EDC-HFL in dataspace projects
Relation to Hyperledger
- EDC-HFL would create an opportunity for the integration of HFL with the emerging dataspaces world, therefore opening the opportunities to have further industrial applications.
- EDC-HFL can be the basis of an incubator project
Mentee Skills
- Ability to work on his/her own and understand complex software architecture and specifications
- Java programming skills
- Basic knowledge on Hyperledger Fabric and chaincode development
- Experience with Private Data Collections is a plus
- Knowledge on Eclipse (project structure, extension mechanisms) is a plus
- An orientation towards industrial use cases is a plus
Future plans
There are several ongoing initiatives for dataspaces which might make use of EDC-HFL, in several application fields (educational data, industrial data, health data, etc.). In addition, such a component could facilitate further, more complex integration of HFL with the data spaces world.
Mentor(s) Names and Contact Info
László Gönczy, associate professor, gonczy.laszlo@vik.bme.hu, Budapest University of Technology and Economics (BME), Dept. of Measurement and Inf. Systems, Critical Systems Research Group,
Imre Kocsis, assistant professor, kocsis.imre@vik.bme.hu, Budapest University of Technology and Economics (BME), Dept. of Measurement and Inf. Systems, Critical Systems Research Group