Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Knowledge Graphs
2021632 citationsAidan Hogan, Eva Blomqvist et al.ACM Computing Surveysprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Juan Sequeda'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 Juan Sequeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan Sequeda more than expected).
This network shows the impact of papers produced by Juan Sequeda. 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 Juan Sequeda. The network helps show where Juan Sequeda may publish in the future.
Co-authorship network of co-authors of Juan Sequeda
This figure shows the co-authorship network connecting the top 25 collaborators of Juan Sequeda.
A scholar is included among the top collaborators of Juan Sequeda 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 Juan Sequeda. Juan Sequeda is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hogan, Aidan, Eva Blomqvist, Michael Cochez, et al.. (2021). Knowledge Graphs. ACM Computing Surveys. 54(4). 1–37.632 indexed citations breakdown →
4.
Angles, Renzo, Angela Bonifati, Stefania Dumbrava, et al.. (2021). PG-Keys: Keys for Property Graphs. Edinburgh Research Explorer (University of Edinburgh). 2423–2436.20 indexed citations
Sequeda, Juan. (2016). Integrating Relational Databases with the Semantic Web. Texas ScholarWorks (Texas Digital Library).8 indexed citations
10.
Sequeda, Juan & Daniel P. Miranker. (2015). Ultrawrap mapper: A semi-automatic relational database to RDF (RDB2RDF) mapping tool. International Semantic Web Conference. 1486.7 indexed citations
11.
Sequeda, Juan. (2013). On the semantics of R2RML and its relationship with the direct mapping. International Semantic Web Conference. 193–196.2 indexed citations
12.
Miranker, Daniel P., et al.. (2012). Diamond debugger demo: Rete-based processing of linked data. 874.4 indexed citations
13.
Sequeda, Juan, et al.. (2012). On ambiguity and query-specific ontology mapping. 946. 238–239.1 indexed citations
Sequeda, Juan, et al.. (2009). Overcoming database heterogeneity to facilitate social networks: the Colombian displaced population as a case study. UPM Digital Archive (Technical University of Madrid).2 indexed citations
17.
Aitken, Stuart, Dilvan de Abreu Moreira, Chris Mungall, et al.. (2009). OBO & OWL: Roundtrip ontology transformations. 559.1 indexed citations
18.
Sahoo, Satya S., Juan Sequeda, & Ahmed Ezzat. (2009). A Survey of Current Approaches for Mapping of Relational Databases to RDF.117 indexed citations
19.
Sequeda, Juan, et al.. (2008). A bootstrapping architecture for integration of relational databases to the semantic web. International Semantic Web Conference. 30–31.1 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.