Presentation about the applicability of the PhD proposal on the Cuban context. Presented on October 17th, 2019 to the Artificial Intelligence and Patterns Recognition Research Group.

1. Query reverse engineering in the
context of the Semantic Web
Author: Leandro Tabares Martín, M. Sc.
Advisers:
Marc Gyssens, PhD
Nemury Silega-Martínez, PhD

2. ONEI's mission
The National Statistics and Information Office (ONEI) is the part
of the Council of Ministers responsible of methodologically
directing the management of information relevant to the
Government and the application of the state policy in the area of
statistics; responding, in particular, for the management of
information and documents of national interest for the Central
Government, including the official statistics of the country; and
directing the development, implementation and deployment of the
computer applications of the Government Information System
and managing its use in the Government's own network.
http://www.one.cu/queeslaone.htm

3. ONEI's data management
• Data shared through ONEI's web site using PDF documents.
• Difficulties to process the shared data by computers and
humans.
• Problems to reuse the shared data and extract meaningful
information.

4. Research project
• Semantic Web technologies for publishing and consuming
Linked Open Data in Cuba.
• Aims to publish ONEI's data following the Linked Open Data
principles.
• Need to consume the published data.

5. Data consumption scenarios
• Centralized and distributed knowledge graphs based on the
Resource Description Framework data model.
• Dynamic knowledge graphs (periodically updated, both schema
and data).
• Significant volumes of data to process.

6. Data consumption issues
• Aggregation of both, centralized and distributed data to satisfy
information needs.
• Schema changes (ontologies, properties used) makes it difficult
to reuse the same queries.
• Management of huge knowledge graphs.

7. Our approach
To use Query Reverse Engineering (QRE) for satisfying
the information needs.

8. Query Reverse Engineering
Given a database D and a result example T, which is the output
of some known or unknown query Q on D; the goal of QRE is to
reverse engineer a query Q’ such that the output of query Q’ on
database D is equal to T.
Generalization created by Tabares-Martín, L. to the concept given by Trung, Chan and Parthasarathy
(2014) “Query reverse engineering”

9. QRE on ONEI's knowledge graphs
• Automate the aggregation of both centralized and distributed
data to satisfy information needs.
• Face schema and data updates by adapting previously
discovered queries.
• Use of adequate technologies to manage big knowledge graphs.

10. Topics of interest
• Algorithms development for applying QRE on centralized and
distributed knowledge graphs.
• Incremental update of SPARQL queries.
• Application of QRE on Big Data scenarios.

11. Query reverse engineering in the
context of the Semantic Web
Author: Leandro Tabares Martín, M. Sc.
Advisers:
Marc Gyssens, PhD
Nemury Silega-Martínez, PhD