🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Judita Kasperiuniene

Vytautas Magnus University

ORCID: 0000-0001-6851-7637
Social SciencesPsychology

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

N/A
0Author DataRank · unranked

Indexed papers

1in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Global Suicide Mortality Rates (2000–2019): Clustering, Themes, and Causes Analyzed through Machine Learning and Bibliographic Data

International Journal of Environmental Research and Public Health(2024)10.3390/ijerph21091202
Top 59%
0.269DataRank
Top 59%5 citations

Judita Kasperiuniene, Erinija Pranckeviciene

Papers

Driven by 1 paper — median percentile 42. Top paper: “Global Suicide Mortality Rates (2000–2019): Clustering, Themes, and Causes Analyzed through Machine Learning and Bibliographic Data”.

Global Suicide Mortality Rates (2000–2019): Clustering, Themes, and Causes Analyzed through Machine Learning and Bibliographic Data

International Journal of Environmental Research and Public Health(2024)10.3390/ijerph21091202
Top 59%
0.269DataRank
Top 59%5 citations

Judita Kasperiuniene, Erinija Pranckeviciene