DSpace 2.0 Storage Service Implementations Based on Semantic Content Repository - Yigang Zhou
Develop DSpace storage service implementations based on semantic content repositories (TripleStore). - Yigang Zhou
Abstract
On the on hand, DSpace 2.0 has a generalized storage service API which allows a DSpace 2.0 repository to use many possible systems to store digital repository data. On the other hand, semantic content repositories (triplestores) such as Mulgural, Sesame and Tupelo are available for semantic data storage, which are suitable for storing blobs and metadata from DSpace represented in the form of RDF triples. In this project, I will develop DSpace storage service implementations based on semantic content repositories. Finally, I will cooperate with Andrius Blažinskas who is working on another GSoC 2010 project of back-porting DSpace 2.0 storage interfaces to 1.x, to make triplestore storage service ready to use for DSpace 1.x.
Project Title: |
DSpace 2.0 Storage Service Implementations Based on Semantic Content Repository |
Student: |
Yigang Zhou, Wuhan University, P.R. China |
Mentors: |
Mark Diggory |
Contacting author: |
egang DOT zhou AT gmail DOT com |
SCM Location for Project: |
http://scm.dspace.org/svn/repo/sandbox/gsoc/2010/triplestore/ |
Architecture
The design principles of the architecture should be:
- The triplestore StorageService can be compatible to all kinds of semantic data storages (e.g. Sesame, Jena, etc.), through different configuration settings.
- Other new semantic data storages (e.g. Mulgural) can be easily plugin into the architecture without much efforts and need not modify code of the API.
- The triplestore StorageService should be able to accommodate both blobs (binary/textual data) and metadata information.
Figure 1. UML Diagram
As is shown in Figure 1, we have a TupeloStorageService