Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Session Overview
Funding and Policy 1
Monday, 03/July/2023:
11:20am - 12:40pm

Session Chair: Katy Borner
Location: IMU Frangipani (Mezzanine Level)

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11:20am - 11:40am

Identification and assessment of datasets resulting from federally funded research: A Case Study of NIAID-funded projects

Seth Schimmel1, Samuel Scribner1, Christopher A Wolcott1, Nakita Pradham1, Sydney Foote2, Jane Lockmuller2, Wilbert Van Panhuis2, Holly Noelle Wolcott1

1Digital Science, United States of America; 2Office of Data Science and Emerging Technologies, National Institute of Allergy and Infectious Diseases, United Sates of America;

Projects funded by the National Institute of Allergy and Infectious Diseases (NIAID) are generating large, diverse, complex datasets that are stored in an array of disparate repositories. To maximize the benefit of these data and conform with policy changes around federally funded research, there has been increased emphasis on data sharing practices and guidelines. Here, we conducted a deep dive of two data intensive projects to better understand current practices. These efforts identified a total of 105 datasets through a combination of automated methods and manual review. Datasets found in Figshare, a generalist repository provided at no charge for researchers, included the richest metadata directly capturing dataset usage and made up the majority of the datasets identified (68 out of 105). Additionally, most of these datasets were viewed or downloaded at least once, though the details of how these data are used or whether they lead to new projects or additional publications has yet to be evaluated. These findings will inform NIAID’s future efforts to monitor compliance with data sharing policies and to demonstrate the value of such policies and more broadly, the value of open data.

Schimmel-Identification and assessment of datasets resulting-214_a.docx
Schimmel-Identification and assessment of datasets resulting-214_b.docx

11:40am - 12:00pm

On the peer review reports: It’s not the size that matters ... really?

Abdelghani Maddi1,2, Luis Miotti1

1Science and Technology Observatory (Hcéres), 2 rue Albert Einstein 75013 Paris; 2GEMASS – CNRS – Sorbonne University, 59/61 rue Pouchet 75017 Paris France;

Scientometers and sociologists of science have spilled much ink on the topic of peer review over the past twenty years given its primordial role in a context marked by the exponential growth of scientific production and the proliferation of predatory journals. Although the topic is addressed under different prisms, few studies have empirically analyzed to what extent it can affect the quality of publications. Here we study the link between the length of reviewers' reports and the citations received by publications. To do this, we used data from the Publons database (58,093 peer review reports). We have adjusted this sample to match the WoS database structure. Our regression results show that peer review positively affects the quality of publications. In other words, the more in-depth (longer) the referees' reports are, the greater the publication improvements will be, resulting in an increase in citations received. This result is important from both the point of view of reviewers and that of journal's chiefs-editors. Even if it is not a remunerated activity, it is important that it be more valued at least within the framework of research evaluation exercises, given its positive impact on science.

Maddi-On the peer review reports-253.docx

12:00pm - 12:20pm

Distribution of Researcher-Level Funding Allocation among U.S. federal funding agencies

Deanna Zarrillo1, Yongjun Zhu2, Erjia Yan1

1College of Computing and Informatics, Drexel University, Philadelphia (U.S.A.); 2Department of Library and Information Science, Yonsei University, Seoul, 03722 (Republic of Korea);

This research-in-progress paper outlines the data collection approach and preliminary results of a study looking at the distribution of research funding from U.S. federal agencies. The goal of this project is to see whether the Matthew Effect, or cumulative advantage, can be found in the distribution of federal funding at the researcher level. The hypothesis of this study is that fewer PIs are being awarded larger proportions of the overall funding pool. This project studies the distribution of the number of grants and amount of funding per primary investigator awarded by eight federal funding agencies from 2008 to 2020. The preliminary results show that the concentration of funding varies across agencies.

Zarrillo-Distribution of Researcher-Level Funding Allocation among US federal funding agencies-273_a.docx
Zarrillo-Distribution of Researcher-Level Funding Allocation among US federal funding agencies-273_b.docx

12:20pm - 12:40pm

The effect of bibliometric research performance assessment on the specialization vs diversification strategies of scientists

Giovanni Abramo1, Ciriaco Andrea D’Angelo2, Flavia Di Costa2

1National Research Council of Italy, Italy; 2University of Rome “Tor Vergata”, Italy;

A side effect of several research evaluation schemes adopted by governments and research organizations is the discouragement of research diversification and cross-discipline fertilization, which are crucial for major global scientific challenges. This work intends to contribute to the literature stream investigating such initiatives’ effects on scientists' specialization/diversification strategies. To this purpose, we analyze the response of academics to the introduction of the national scientific accreditation (ASN) for professorship introduced in Italy in 2012. We will conduct a longitudinal disciplinary analysis of the publications of each Italian professor in the sciences (over 25.000), accounting for those individual and contextual variables that might moderate the opportunistic response to the ASN incentive scheme.

Abramo-The effect of bibliometric research performance assessment-135.docx

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