Irene V. Pasquetto

1.2k total citations
28 papers, 558 citations indexed

About

Irene V. Pasquetto is a scholar working on Information Systems, Information Systems and Management and Sociology and Political Science. According to data from OpenAlex, Irene V. Pasquetto has authored 28 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Information Systems, 14 papers in Information Systems and Management and 11 papers in Sociology and Political Science. Recurrent topics in Irene V. Pasquetto's work include Research Data Management Practices (15 papers), Scientific Computing and Data Management (11 papers) and Data Quality and Management (7 papers). Irene V. Pasquetto is often cited by papers focused on Research Data Management Practices (15 papers), Scientific Computing and Data Management (11 papers) and Data Quality and Management (7 papers). Irene V. Pasquetto collaborates with scholars based in United States, Canada and United Kingdom. Irene V. Pasquetto's co-authors include Christine L. Borgman, Britt Paris, Morgan Currie, Michelle A. Amazeen, Roderic Crooks, Peter T. Darch, Milena S. Golshan, Shubham Atreja, Matthew Baum and Eaman Jahani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Journal of Documentation.

In The Last Decade

Irene V. Pasquetto

24 papers receiving 533 citations

Peers

Irene V. Pasquetto
Comparison fields: 5 of 94
  • Information Systems 240
  • Sociology and Political Science 185
  • Information Systems and Management 175
  • Management Science and Operations Research 102
  • Artificial Intelligence 93
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Citations per field, relative to Irene V. Pasquetto
Irene V. Pasquetto · 1×
Citations per year, relative to Irene V. Pasquetto
Irene V. Pasquetto · 1×

Countries citing papers authored by Irene V. Pasquetto

Since Specialization
Citations

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

Fields of papers citing papers by Irene V. Pasquetto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Irene V. Pasquetto. 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 Irene V. Pasquetto. The network helps show where Irene V. Pasquetto may publish in the future.

Co-authorship network of co-authors of Irene V. Pasquetto

This figure shows the co-authorship network connecting the top 25 collaborators of Irene V. Pasquetto. A scholar is included among the top collaborators of Irene V. Pasquetto 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 Irene V. Pasquetto. Irene V. Pasquetto 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
# Work Indexed citations
1 1
2 2
3 0
4 7
5 0
6 2
7 7
8 28
9 16
10
All disinformation is local: A reflection on the need and possibility of measuring impact
1
11
Our knowledge of knowledge infrastructures: Lessons learned and future directions
4
12 57
13 2
14 20
15 13
16 1
17
PhD Dissertation - From Open Data to Knowledge Production: Biomedical Data Sharing and Unpredictable Data Reuses
2
18 19
19 58
20 36

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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