Enrico Daga

38 papers receiving 251 citations

Peers

Enrico Daga
Comparison fields: 5 of 60
  • Artificial Intelligence 151
  • Information Systems 102
  • Management Science and Operations Research 47
  • Computer Networks and Communications 44
  • Computer Vision and Pattern Recognition 37
Replace Victor de Boer with:
Victor de Boer Netherlands
Alessandro Adamou United Kingdom
Donato Pirozzi Italy
Francesco Poggi Italy
Michiel Hildebrand Netherlands
Albert Meroño-Peñuela United Kingdom
Shigeo Sugimoto Japan
Vassilis Poulopoulos Greece
Ame Elliott United States
Robert Tansley United Kingdom
Enrico Daga relative to Victor de Boer Netherlands Victor de Boer's profile →
Citations per field
00.5×
Victor de Boer · 1×
Citations per year

Countries citing papers authored by Enrico Daga

Since Specialization
Citations

This map shows the geographic impact of Enrico Daga's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Enrico Daga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enrico Daga more than expected).

Fields of papers citing papers by Enrico Daga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Enrico Daga. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Enrico Daga. The network helps show where Enrico Daga may publish in the future.

Co-authorship network of co-authors of Enrico Daga

This figure shows the co-authorship network connecting the top 25 collaborators of Enrico Daga. A scholar is included among the top collaborators of Enrico Daga based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Enrico Daga. Enrico Daga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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12
Modelling and querying lists in RDF: A pragmatic study
4
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14
Characterizing the Landscape of Musical Data on the Web: State of the Art and Challenges
4
15
Proceedings of the 1st Workshop on Humanities in the Semantic Web co-located with 13th ESWC Conference 2016 (ESWC 2016)
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16
Bottom-Up Ontology Construction with Contento
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BASIL: A Cloud Platform for Sharing and Reusing SPARQL Queries as Web APIs
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Linked Open Data for the Italian PA: The CNR Experience
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About Enrico Daga

Enrico Daga is a scholar working on Music, Artificial Intelligence and Museology, having authored 44 papers that have together received 274 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (23 papers), Service-Oriented Architecture and Web Services (8 papers) and Data Quality and Management (8 papers). The work is most often cited by research in Artificial Intelligence (151 citations), Information Systems (102 citations) and Conservation (14 citations). Enrico Daga has collaborated with scholars based in United Kingdom, Netherlands and Italy. Frequent co-authors include Aldo Gangemi, Enrico Motta, Mathieu d’Aquin, Valentina Presutti, Eva Blomqvist, Paul Mulholland, Alessandro Adamou, Ilaria Tiddi, Emanuele Bastianelli and Andreas L. Opdahl. Their work appears in journals such as IEEE Access, International Journal of Social Robotics and Journal of Web Semantics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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