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

Tullia Padellini

Bank of Italy

ORCID: 0000-0001-8456-0256
MathematicsSocial SciencesEconomics, Econometrics and FinanceComputer ScienceEnvironmental Science

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.

Top 6%percentile
0.268Author DataRank

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.

A Bayesian hierarchical small area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial census data

The Annals of Applied Statistics(2024)10.1214/23-aoas1849
Top 58%
0.268DataRank
Top 58%4 citations

Rachel C. Nethery, Tullia Padellini, Jarvis T. Chen, Brent A. Coull, Frédéric B Piel +4 more

Papers

Driven by 5 papers — median percentile 42. Top paper: “A Bayesian hierarchical small area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial census data”.

A Bayesian hierarchical small area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial census data

The Annals of Applied Statistics(2024)10.1214/23-aoas1849
Top 58%
0.268DataRank
Top 58%4 citations

Rachel C. Nethery, Tullia Padellini, Jarvis T. Chen, Brent A. Coull, Frédéric B Piel +4 more

Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis

Environment International(2020)10.1016/j.envint.2020.106316
N/A
0DataRank · unranked
142 citations

Tullia Padellini, James E. Bennett, Bethan Davies, Majid Ezzati, Marta Blangiardo +1 more

Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis

medRxiv(2020)10.1101/2020.08.10.20171421
N/A
0DataRank · unranked
25 citations

Tullia Padellini, James E. Bennett, Bethan Davies, Majid Ezzati, Marta Blangiardo +1 more

Response to “Re: Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis”

Environment International(2021)10.1016/j.envint.2021.106427
N/A
0DataRank · unranked
2 citations

Tullia Padellini, James E. Bennett, Bethan Davies, Majid Ezzati, Marta Blangiardo +1 more

Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: A population-based ecological study

The Lancet Regional Health - Europe(2022)10.1016/j.lanepe.2022.100322
N/A
0DataRank · unranked
45 citations

Radka Jersakova, Peter J. Diggle, Chris Holmes, Ruairidh King, Brieuc Lehmann +5 more