What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Operating system
His primary areas of study are Query language, RDF, Information retrieval, Temporal database and RDF query language.
His Query language research incorporates themes from Semantics, GeoSPARQL, Data model and Geospatial analysis.
Manolis Koubarakis studies SPARQL which is a part of RDF.
His SPARQL research is multidisciplinary, relying on both Semantic Web Rule Language and Linked data.
His study in Information retrieval is interdisciplinary in nature, drawing from both Hash table and Data mining.
In his study, Theoretical computer science is strongly linked to Temporal information, which falls under the umbrella field of Temporal database.
His most cited work include:
- Telos: representing knowledge about information systems (712 citations)
- Composing cardinal direction relations (140 citations)
- Spatio-Temporal Databases: The CHOROCHRONOS Approach (132 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Information retrieval, RDF, Geospatial analysis, World Wide Web and SPARQL.
The Information retrieval study combines topics in areas such as Data modeling and Theoretical computer science.
His studies deal with areas such as Time complexity, Qualitative reasoning and Data mining as well as Theoretical computer science.
His RDF course of study focuses on Scalability and Distributed computing.
His Geospatial analysis study combines topics from a wide range of disciplines, such as Linked data, GeoSPARQL, Data science and Open data.
In general World Wide Web, his work in Semantic Web is often linked to Publication and Digital library linking many areas of study.
He most often published in these fields:
- Information retrieval (23.32%)
- RDF (21.52%)
- Geospatial analysis (19.73%)
What were the highlights of his more recent work (between 2017-2021)?
- Geospatial analysis (19.73%)
- RDF (21.52%)
- SPARQL (16.14%)
In recent papers he was focusing on the following fields of study:
Geospatial analysis, RDF, SPARQL, Linked data and GeoSPARQL are his primary areas of study.
The various areas that Manolis Koubarakis examines in his Geospatial analysis study include Spatial analysis, Information retrieval, Search engine indexing, Cloud computing and Data science.
His RDF study deals with Scalability intersecting with Joins and Parallel computing.
He combines subjects such as Programming language and Translation with his study of SPARQL.
His study explores the link between Linked data and topics such as Data access that cross with problems in Library science, Key and Axiom.
His GeoSPARQL study also includes
- Benchmark that intertwine with fields like Database,
- Relational database and related Measure, Ontology, Data visualization and Visualization.
Between 2017 and 2021, his most popular works were:
- The return of jedAI: end-to-end entity resolution for structured and semi-structured data (19 citations)
- GeoTriples: Transforming geospatial data into RDF graphs using R2RML and RML mappings (17 citations)
- Template-Based Question Answering over Linked Geospatial Data (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Programming language
Manolis Koubarakis mostly deals with Geospatial analysis, Linked data, SPARQL, World Wide Web and Information retrieval.
His research investigates the connection with Geospatial analysis and areas like GeoSPARQL which intersect with concerns in Natural language, Data science, Question answering, Service and Benchmark.
His Linked data study incorporates themes from Change detection, Cloud computing and Data mining.
In most of his SPARQL studies, his work intersects topics such as Database.
His work on Open government as part of general World Wide Web study is frequently linked to Copernicus, Named-entity recognition and Legislation, bridging the gap between disciplines.
RDF and Knowledge graph are subfields of Information retrieval in which his conducts study.
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