This map shows the geographic impact of Kai Eckert'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 Kai Eckert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Eckert more than expected).
This network shows the impact of papers produced by Kai Eckert. 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 Kai Eckert. The network helps show where Kai Eckert may publish in the future.
Co-authorship network of co-authors of Kai Eckert
This figure shows the co-authorship network connecting the top 25 collaborators of Kai Eckert.
A scholar is included among the top collaborators of Kai Eckert 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 Kai Eckert. Kai Eckert is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Yin, Dan Wu, Loni Hagen, et al.. (2022). Data science curriculum in the iField. Journal of the Association for Information Science and Technology. 74(6). 641–662.7 indexed citations
8.
Lauscher, Anne, Kai Eckert, Ansgar Scherp, et al.. (2018). Linked Open Citation Database. ZBW Publication Archive (ZBW – Leibniz Information Centre for Economics). 109–118.9 indexed citations
9.
Lauscher, Anne, Goran Glavaš, & Kai Eckert. (2017). University of Mannheim @ CLSciSumm-17: Citation-Based Summarization of Scientific Articles Using Semantic Textual Similarity. MADOC (University of Mannheim). 33–42.13 indexed citations
Bizer, Christian, Kai Eckert, Stefano Faralli, et al.. (2016). A large database of hypernymy relations extracted from the Web. Language Resources and Evaluation. 360–367.36 indexed citations
13.
Eckert, Kai, et al.. (2015). Guidance, please! towards a framework for RDF-based constraint languages. International Conference on Dublin Core and Metadata Applications. 95–111.4 indexed citations
14.
Eckert, Kai, Daniel Faria, Alfio Ferrara, et al.. (2014). Results of the Ontology Alignment Evaluation Initiative 2014. SPIRE - Sciences Po Institutional REpository.11 indexed citations
15.
Eckert, Kai, et al.. (2014). Towards description set profiles for RDF using SPARQL as intermediate language. International Conference on Dublin Core and Metadata Applications. 129–137.6 indexed citations
16.
Eckert, Kai, et al.. (2014). Requirements on RDF constraint formulation and validation. International Conference on Dublin Core and Metadata Applications. 95–108.9 indexed citations
17.
Eckert, Kai. (2013). Provenance and annotations for linked data. International Conference on Dublin Core and Metadata Applications. 9–18.4 indexed citations
18.
Eckert, Kai, et al.. (2011). Extending DCAM for metadata provenance. UPM Digital Archive (Technical University of Madrid). 12–25.1 indexed citations
19.
Eckert, Kai, et al.. (2009). A unified approach for representing metametadata. MADOC (University of Mannheim). 21–29.4 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.