Martín Ugarte

832 total citations
20 papers, 435 citations indexed

About

Martín Ugarte is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Martín Ugarte has authored 20 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Networks and Communications, 11 papers in Artificial Intelligence and 8 papers in Information Systems. Recurrent topics in Martín Ugarte's work include Advanced Database Systems and Queries (12 papers), Semantic Web and Ontologies (9 papers) and Data Management and Algorithms (6 papers). Martín Ugarte is often cited by papers focused on Advanced Database Systems and Queries (12 papers), Semantic Web and Ontologies (9 papers) and Data Management and Algorithms (6 papers). Martín Ugarte collaborates with scholars based in Belgium, Chile and Germany. Martín Ugarte's co-authors include Juan L. Reutter, Domagoj Vrgoč, Fernando Suárez, Stijn Vansummeren, Muhammad Zaffwan Idris, Felipe Bravo-Márquez, Steve Reeves, Marcelo Arenas, Cristian Riveros and Wolfgang Lehner and has published in prestigious journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record and ACM Transactions on Database Systems.

In The Last Decade

Martín Ugarte

20 papers receiving 422 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Martín Ugarte Belgium 10 220 153 146 94 58 20 435
Sven Groppe Germany 13 354 1.6× 365 2.4× 148 1.0× 105 1.1× 77 1.3× 108 583
Luke K. McDowell United States 13 100 0.5× 229 1.5× 129 0.9× 37 0.4× 66 1.1× 32 431
Lisa Amini United States 13 495 2.3× 291 1.9× 197 1.3× 115 1.2× 88 1.5× 34 727
Christian A. Lang United States 14 252 1.1× 96 0.6× 102 0.7× 84 0.9× 77 1.3× 36 496
Chuntao Jiang China 9 85 0.4× 182 1.2× 160 1.1× 59 0.6× 146 2.5× 22 454
Irene Finocchi Italy 15 323 1.5× 186 1.2× 144 1.0× 75 0.8× 81 1.4× 63 658
Krishnamurthy Viswanathan United States 8 185 0.8× 270 1.8× 100 0.7× 73 0.8× 33 0.6× 31 405
Aibo Song China 12 360 1.6× 155 1.0× 357 2.4× 50 0.5× 55 0.9× 67 609
Michelangelo Diligenti Italy 13 179 0.8× 408 2.7× 416 2.8× 120 1.3× 168 2.9× 39 836
Ceriel J. H. Jacobs Netherlands 13 403 1.8× 219 1.4× 194 1.3× 25 0.3× 31 0.5× 28 635

Countries citing papers authored by Martín Ugarte

Since Specialization
Citations

This map shows the geographic impact of Martín Ugarte'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 Martín Ugarte with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martín Ugarte more than expected).

Fields of papers citing papers by Martín Ugarte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martín Ugarte. 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 Martín Ugarte. The network helps show where Martín Ugarte may publish in the future.

Co-authorship network of co-authors of Martín Ugarte

This figure shows the co-authorship network connecting the top 25 collaborators of Martín Ugarte. A scholar is included among the top collaborators of Martín Ugarte 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 Martín Ugarte. Martín Ugarte 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
1.
Eyheramendy, S., Pedro A. Saa, Eduardo A. Undurraga, et al.. (2021). Screening of COVID-19 cases through a Bayesian network symptoms model and psychophysical olfactory test. iScience. 24(12). 103419–103419. 2 indexed citations
2.
Riveros, Cristian, et al.. (2021). A Formal Framework for Complex Event Recognition. ACM Transactions on Database Systems. 46(4). 1–49. 10 indexed citations
3.
Arenas, Marcelo, et al.. (2020). Cryptocurrency Mining Games with Economic Discount and Decreasing Rewards. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations
4.
Riveros, Cristian, et al.. (2020). On the Expressiveness of Languages for Complex Event Recognition. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 5 indexed citations
5.
Florenzano, Fernando, Cristian Riveros, Martín Ugarte, Stijn Vansummeren, & Domagoj Vrgoč. (2020). Efficient Enumeration Algorithms for Regular Document Spanners. ACM Transactions on Database Systems. 45(1). 1–42. 8 indexed citations
6.
Bravo-Márquez, Felipe, Steve Reeves, & Martín Ugarte. (2019). Proof-of-Learning: A Blockchain Consensus Mechanism Based on Machine Learning Competitions. Research Commons (University of Waikato). 119–124. 63 indexed citations
7.
Idris, Muhammad Zaffwan, Martín Ugarte, Stijn Vansummeren, Hannes Voigt, & Wolfgang Lehner. (2019). Efficient Query Processing for Dynamically Changing Datasets. ACM SIGMOD Record. 48(1). 33–40. 9 indexed citations
8.
Riveros, Cristian, et al.. (2019). A Formal Framework for Complex Event Processing. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 8 indexed citations
9.
Idris, Muhammad Zaffwan, Martín Ugarte, Stijn Vansummeren, Hannes Voigt, & Wolfgang Lehner. (2019). General dynamic Yannakakis: conjunctive queries with theta joins under updates. The VLDB Journal. 29(2-3). 619–653. 15 indexed citations
10.
Idris, Muhammad Zaffwan, Martín Ugarte, Stijn Vansummeren, Hannes Voigt, & Wolfgang Lehner. (2018). Conjunctive queries with inequalities under updates. Proceedings of the VLDB Endowment. 11(7). 733–745. 12 indexed citations
11.
Arenas, Marcelo & Martín Ugarte. (2017). Designing a Query Language for RDF. ACM Transactions on Database Systems. 42(17). 2. 1 indexed citations
12.
Artikis, Alexander, Alessandro Margara, Martín Ugarte, Stijn Vansummeren, & Matthias Weidlich. (2017). Complex Event Recognition Languages. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 7–10. 20 indexed citations
13.
Arenas, Marcelo & Martín Ugarte. (2017). Designing a Query Language for RDF. ACM Transactions on Database Systems. 42(4). 1–46. 11 indexed citations
14.
Idris, Muhammad Zaffwan, Martín Ugarte, & Stijn Vansummeren. (2017). The Dynamic Yannakakis Algorithm. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 1259–1274. 45 indexed citations
15.
Arenas, Marcelo & Martín Ugarte. (2016). Designing a Query Language for RDF. 70. 225–236. 4 indexed citations
16.
Reutter, Juan L., et al.. (2016). Foundations of JSON Schema. 263–273. 201 indexed citations
17.
Ugarte, Martín, et al.. (2015). A preliminary investigation into SPARQL query complexity and federation in Bio2RDF. CEUR Workshop Proceedings. 1378. 196–204. 2 indexed citations
18.
Kostylev, Egor V., Juan L. Reutter, & Martín Ugarte. (2015). CONSTRUCT Queries in SPARQL. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 31. 229. 10 indexed citations
19.
Arenas, Marcelo, et al.. (2014). Discovering XSD Keys from XML Data. ACM Transactions on Database Systems. 39(4). 1–49. 3 indexed citations
20.
Arenas, Marcelo, et al.. (2013). Discovering XSD keys from XML data. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 61–72. 5 indexed citations

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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