LoDGoV : Generate, manage, preserve, share and protect resources in the Web of Data¶
- LoDGoV : Generate, manage, preserve, share and protect resources in the Web of Data
CONCEPTS AND OBJECTIVES¶
The Linked Data paradigm involves practices to publish, share, and connect data on the Web, and offers a new way of data integration and interoperability. The driving force to implement Linked Data is the RDF technology. The basic principles of the Linked Data paradigm is (a) use the RDF data model to publish structured data on the Web, and (b) use RDF links to interlink data from different data sources. Linked Data technologies have given rise to the Web of Data. The Web of Data extents current Web to a global data space connecting data from diverse domains. This gives added value for decision support and business intelligence applications, and enables new types of services that operate on top of an unbound, global data space and not on a fixed set of data sources as in Web 2.0 mashups. The Web of Data is impelled by the current trend towards Open Data, i.e., public data which are easily discoverable, accessible, and available to people without any restriction. Linked Open Data (LOD) serve a great cause, enabling transparency, accountability and good governance for public administrations. This is evident from international (e.g., data.gov.uk), and national efforts (e.g., geodata.gov.gr, which was developed by applicant’s research team in IMIS institute). As a side effect, LOD promote sustainable growth and offer a new paradigm for business models and public/private partnerships.
Data Governance is an emerging field that brings together data quality, data management, and process management, regarding the handling of data in an organization. It involves controlling the full lifecycle of data produced and consumed within an organization: generation, assessment, management and processing, monitoring, maintenance and protection. Further, it offers technical and organizational solutions for integrating external data sources transparently. The goals of Data Governance include improving decision making, ensuring data processing transparency, adopting common approaches to data maintenance, and minimizing rework.
To achieve its goal, the LODGOV project will pursue the following challenging scientific and technological objectives:
LODGOV’s vision is to establish applicant’s research team as the premium R&D pole in LOD management and governance. The aim is to provide innovative technologies for best governance and curation practices for LOD in order to produce sustainable LOD ecosystems. LODGOV will handle the full lifecycle of LOD ecosystems, from data extraction, storage and maintenance, to monitoring, protection and repair.
- Effective methods for exposing large volumes of structured and unstructured data as LOD.
- Efficient storage solutions for large volumes of LOD.
- Query methods, retrieval algorithms and ranking techniques for LOD.
- Methods for interlink and fuse LOD from different data sources on the Web.
- Models and query languages to represent and query changes in LOD spaces.
- Provenance models and methods to trace the origins and transformations in LOD spaces.
- Design principles and best practices to expose LOD with anonymity guarantees.
- Models and methods to ensure privacy for publishing LOD.
- Timos Sellis, Prof
- Vasilis Christophides, Prof
- Vasilis Vasalos, Prof
- Theodore Dalamagas, Senior Researcher
- Stelios Sartzetakis, Senior Researcher
- Katerina Gkirtzou, Postdoc Researcher
- Papadakis Giorgos, Postdoc Researcher
- Konstantinos Karozos, PhD student
- Thanasis Vergoulis, PhD student
- Giorgos Alexiou, PhD student
- Panos Georgantas, Tech staff
- WP1 (Study and analysis of LOD landscape, 6M). Prior to any core research activity, WP1 analyses the current landscape in Semantic Web and LOD, sets up the common ground, and defines the S&T agenda.
- WP2 (LOD management, 18M). WP2 starts with an extensive study of RDF storage and query methods. Then, the involved tasks include: (a) developing efficient solutions for exposing and fusing large LOD volumes from heterogeneous sources, (b) developing efficient co-reference methods to automatically and effectively interlink LOD datasets, (c) implementing indexing structures and ranking methods to support efficient LOD keyword search, (d) developing methods to support efficient retrieval and ranking of LOD entities, and (e) designing optimization methods for processing SPARQL queries on LOD.
- WP3 (LOD dynamics, 18M). WP3 will start with an extensive study of state-of-the-art methods in data evolution and change management. Then, the involved tasks include: (a) developing models and methods to support LOD provenance, (b) developing models and methods to support LOD preservation, (c) designing query languages to explore LOD trails, (d) designing methods and metrics to evaluate LOD ecosystems with respect to its ability to sustain and adapt to evolution events.
- WP4 (LOD privacy, 18M). WP4 will start with an extensive study of state-of-the-art for privacy-preserving methods in data publishing. Then, the involved tasks include: (a) exploring privacy-threatening scenarios in the LOD publication, as well as defining the privacy requirements and guarantees that must be maintained, (b) providing design principles and best practices to expose LOD with anonymity guarantees, (c) developing LOD anonymization methods.
- WP5 (LOD governance, 12M). WP2, WP3, and WP4 form the basis for the LOD Data Governance infrastructure, envisioned by LODGOV. Thus, WP5 integrates the outcome of WP2, WP3 and WP4, providing best practices for designing and evaluation of sustainable LOD ecosystems.
- WP6 (Evaluation, 6M). In WP6, the LODGOV team will validate the LODGOV models, methods and algorithms for LOD governance. It is important to note that the host organization maintains two Open Data services: one in the area of life science data, and one in the area of governmental open data (see also Section 1.1). Both services can be used as excellent testbeds for validating LODGOV’s technology, and this is an important advantage for LODGOV project.
- WP7 (Management and dissemination, 36M). Finally, to ensure effective planning and implementation of project activities, and promoting project results, WP7 is foreseen.
|Linked Open Data Study and Analysis Report||Technical Report||Deliverable 1.1|
|D3.1: Models and query languages for LOD changes||Technical Report||Deliverable 3.1|
|D3.2: Models and methods for LOD provenance and preservation||Technical Report||Deliverable 3.2|
|Privacy models for LOD||Technical Report||Deliverable 4.1 (prepared for publ. submission, ask to download)|
|Entity Resolution in the Web of Data pdf Website||Tutorial|
|D2.1: Linked Open Data integration methods||Deliverable 2.1||link|
|Models and query languages for changes in LOD - Tool||Deliverable 3.1||link|