Link Function: information

One of the newest types of multimedia involves body-connected interfaces, usually termed haptics. Haptics may use stylus-based tactile interfaces, glove-based systems, handheld controllers, balance boards, or other custom-designed body-computer interfaces. How well do these interfaces help students learn Science, Technology, Engineering, and Mathematics (STEM)? We conducted an updated review of learning STEM with haptics, applying meta-analytic techniques to 21 published articles reporting on 53 effects for factual, inferential, procedural, and transfer STEM learning. This deposit includes the data extracted from those articles and comprises the raw data used in the meta-analytic analyses.

The Cline Center Global News Index is a searchable database of textual features extracted from millions of news stories, specifically designed to provide comprehensive coverage of events around the world. In addition to searching documents for keywords, users can query metadata and features such as named entities extracted using Natural Language Processing (NLP) methods and variables that measure sentiment and emotional valence. Archer is a web application purpose-built by the Cline Center to enable researchers to access data from the Global News Index. Archer provides a user-friendly interface for querying the Global News Index (with the back-end indexing still handled by Solr). By default, queries are built using icons and drop-down menus. More technically-savvy users can use Lucene/Solr query syntax via a ‘raw query’ option. Archer allows users to save and iterate on their queries, and to visualize faceted query results, which can be helpful for users as they refine their queries. Additional Resources: - Access to Archer and the Global News Index is limited to account-holders. If you are interested in signing up for an account, you can fill out the Archer User Information Form. - Current users who would like to provide feedback, such as reporting a bug or requesting a feature, can fill out the Archer User Feedback Form. - The Cline Center sends out periodic email newsletters to the Archer Users Group. Please fill out this form to subscribe to Archer Users Group. Citation Guidelines: 1) To cite the GNI codebook (or any other documentation associated with the Global News Index and Archer) please use the following citation: Cline Center for Advanced Social Research. 2020. Global News Index and Extracted Features Repository [codebook]. Champaign, IL: University of Illinois. doi:10.13012/B2IDB-5649852_V1 2) To cite data from the Global News Index (accessed via Archer or otherwise) please use the following citation (filling in the correct date of access): Cline Center for Advanced Social Research. 2020. Global News Index and Extracted Features Repository [database]. Champaign, IL: University of Illinois. Accessed Month, DD, YYYY. doi:10.13012/B2IDB-5649852_V1

About this dataset

Context

The dataset tabulates the population of Illinois by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Illinois across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.6% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Illinois is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Illinois total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Race & Ethnicity. You can refer the same here

Comprehensive dataset of 15 Student unions in Illinois, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Description

The research employed a mixed methods online survey to understand better the meaning, use, and development of academic research software at the University of Illinois Urbana-Champaign. Other objectives include understanding academic research software support and training needs to make projects successful at Illinois, as well as investigating the use of generative AI tools in using and creating research software.

At the beginning of the survey, all participants gave informed consent. The University of Illinois Urbana-Champaign Institutional Review Board (IRB Protocol no.: Project IRB24-0989) reviewed the study and gave it an exempt determination.

Data collection took place from August 2024 to October 2024. Prior to data analysis, identifiable respondent details were removed during the data cleaning process. Not Applicable and Unsure style responses were used for descriptive statistics, but these responses were excluded for inferential statistics.

Survey design

At the beginning of the online survey, a consent form was provided based on guidelines from the University of Illinois Institutional Review Board to the respondents stating the aims of the study, its benefits and risks, ethical guidelines, being a voluntary survey for participation and withdrawal, privacy and confidentiality, data security, estimated time for survey completion, and contact information of researchers for asking questions. Respondents clicked to indicate their consent. Survey questions were divided into four parts: demographic information, using software for research, creating software for research, and the protocol of citing software for research. The survey had to stop points, whereby not all questions applied to respondents, which led to different sample sizes at the stop points. At the opening of the survey, the number of respondents was 251 with the funding demographic question being answered by all respondents, while other demographic questions had between 225 and 228 respondents answering them. For the first stop question, using research software in their research, the total respondents was 212, and at the last stop question, respondents considering themselves to be research developers, the total number of respondents was 74. The last question of the survey was answered by 71 respondents. Respondents may also have left the survey for other reasons. The questions were primarily closed-type questions with single choice, multiple choice, or Likert scale, as well as a few open-ended questions. Likert scale responses were created utilizing validated scales from Vagias' (2006) Likert Type Scale Response Anchors.

Sampling

Survey Respondents’ Demographics

While most respondents were Tenure Track Faculty (34.7%, f=227), other key categories included Principal Investigator (22.4%, f=227) and Research Scientist (12.1%, f=227). Computer Science, Information Science, Mathematics, and Engineering fields combined for 16% (f=228) of the respondents surveyed, but it should be noted the remaining respondents were from various academic fields across campus from various arts, humanities, and social science fields (25%, f=228) to agriculture (10%, f=228), education (5%, f=228), economics (3%, f=228), medical sciences (4%, f=228), and politics and policy/law (1%, f=228). Most respondents were likely to receive funding from various government agencies. A more detailed breakdown of the demographic information can be found in the supplemental figures. Of the 74 respondents who answered whether they were a research software developer, most respondents did not consider themselves a research software developer, with respondents stating Not at All (39%, n=74) and Slightly (22%, n=74). In addition, open-ended questions asked for further detail about research software titles used in research, research software developer challenges, how generative AI assisted in creating research software, and how research software is preserved (e.g., reproducibility).

Table 1: Survey Respondents’ Demographics

Characteristics

Respondent (%)

Age

 18-24

 25-34

 35-44

 45-54

 55-64

 Over 64

 Preferred Not Answer

3%

14%

33%

27%

14%

7%

2%

Gender

 Woman

 Man

 Non-binary / non-conforming

 Prefer not to answer

49%

44%

2%

4%

Race

 Asian

 Black or African American

 Hispanic or Latino

 Middle Eastern or North African (MENA; new)

 White

 Prefer not to answer

 Other

12%

5%

6%

1%

67%

8%

1%

Highest Degree

 Bachelors

 Masters

 Professional degree (e.g., J.D.)

 Doctorate

6%

19%

5%

70%

Professional Title

 Tenure Track Faculty

 Principal Investigator

 Research Scientist

 Staff

 Research Faculty

 Other

 Teaching Faculty

 Postdoc

 Research Assistant

 Research Software Engineer

35%

22%

12%

8%

7%

4%

4%

4%

2%

2%

Academic Field

 Biological Sciences

 Other

 Agriculture

 Engineering

 Psychology

 Earth Sciences

 Physical Sciences

 Education

 Medical & Health Sciences

 Computer Science

 Library

 Chemical Sciences

 Human Society

 Economics

 Information Science

 Environment

 Veterinary

 Mathematical Sciences

 History

 Architecture

 Politics and Policy

 Law

18%

10%

10%

9%

8%

6%

6%

5%

4%3%

3%

3%

3%

3%

2%

2%

2%

2%

1%

1%

1%

0%

Years Since Last Degree

 Less than 1 Year

 1-2 Years

 3-5 Years

 6-9 Years

 10-15 Years

 More than 15 Years

4%

8%

11%

14%

24%

40%

Receive Funding

 Yes

 No

73%

27%

Funders for Research

 Other

 National Science Foundation (NSF)

 United States Department of Agriculture (USDA)

 National Institute of Health (NIH)

 Department of Energy (DOE)

 Department of Defense (DOD)

 Environmental Protection Agency (EPA)

 National Aeronautics and Space Administration (NASA)

Bill and Melinda Gates Foundation

Advanced Research Projects Agency - Energy (ARPA-E)

Institute of Education Sciences

Alfred P. Sloan Foundation

W.M. Keck Foundation

Simons Foundation

Gordon and Betty Moore Foundation

Department of Justice (DOJ)

National Endowment for the Humanities (NEH)

Congressionally Directed Medical Research Programs (CDMRP)

Andrew W. Mellon Foundation

22%

18%

18%

11%

9%

5%

4%

4%

2%

2%

1%

1%

1%

1%

1%

1%

0%

0%

0%

Table 2: Survey Codebook

QuestionID

Variable

Variable Label

Survey Item

Response Options

1

age

Respondent’s Age

Section Header:

Demographics Thank you for your participation in this survey today! Before you begin to answer questions about academic research software, please answer a few demographic questions to better contextualize your responses to other survey questions.

What is your age?

Select one choice.

Years

1-Under 18

2-18-24

3-25-34

4-35-44

5-45-54

6-55-64

7-Over 64

8-Prefer not to answer

2

gender

Respondent’s Gender

What is your gender?

Select one choice.

1-Female

2-Male

3-Transgender

4-Non-binary / non-conforming

5-Prefer not to answer

6-Other:

3

race

Respondent’s Race

What is your race?

Select one choice.

1-American Indian or Alaska Native

2-Asian

3-Black or African American

4-Hispanic or Latino

5-Middle Eastern or North African (MENA; new)

6-Native Hawaiian or Pacific Islander

7-White

8-Prefer not to answer

9-Other:

4

highest_degree

Respondent’s Highest Degree

What is the highest degree you have completed?

Select one choice.

1-None

2-High school

3-Associate

4-Bachelor's

5-Master's

6-Professional degree (e.g., J.D.)

7-Doctorate

8-Other:

5

professional_title

Respondent’s Professional Title

What is your professional title?

Select all that apply.

1-professional_title_1

Principal Investigator

2-professional_title_2

Tenure Track Faculty

3-professional_title_3

Teaching Faculty

4-professional_title_4

Research Faculty

5-professional_title_5

Research Scientist

6-professional_title_6

Research Software Engineer

7-professional_title_7

Staff

8-professional_title_8

Postdoc

9-professional_title_9

Research Assistant

10-professional_title_10

Other:

6

academic_field

Respondent’s most strongly identified Academic Field

What is the academic field or discipline you most strongly identify with (e.g., Psychology, Computer Science)?

Select one choice.

1-Chemical sciences

2-Biological sciences

3-Medical & health sciences

4-Physical sciences

5-Mathematical sciences

6-Earth sciences

7-Agriculture

8-Veterinary

9-Environment

10-Psychology

11-Law

12-Philosophy

13-Economics

14-Human society

15-Journalism

16-Library

17-Education

18-Art & Design Management

19-Engineering

20-Language

21-History

22-Politics and policy

23-Architecture

24-Computer Science

25-Information science

26-Other:

7

years_since_last_degree

Number of years since last respondent’s last degree

How many years since the award of your last completed degree?

Select one choice.

1-Less than 1 year

2-1-2 years

3-3-5 years

4-6-9 years

5-10-15 years

6-More than 15 years

8

receive_funding_for_research

Whether respondent received funding for research

Do you receive funding for your research?

1-Yes

0-No

9

funders_for_research

Respondent’s funding sources if they answered yes in Question 8

Who funds your research or work (e.g., NIH, Gates Foundation)?

Select all that apply.

1-funders_for_research_1

United States Department of Agriculture (USDA)

2-funders_for_research_2

Department of Energy (DOE)

3-funders_for_research_3

National Science

Qualitative Data collected from the websites of undergraduate research journals between October, 2014 and May, 2015. Two CSV files. The first file, "Sample", includes the sample of journals with secondary data collected. The second file, "Population", includes the remainder of the population for which secondary data was not collected. Note: That does not add up to 800 as indicated in article, rows were deleted for journals that had broken links or defunct websites during random sampling process.

About this dataset

Context

The dataset tabulates the population of Illinois by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Illinois. The dataset can be utilized to understand the population distribution of Illinois by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Illinois. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Illinois.

Key observations

Largest age group (population): Male # 30-34 years (437,015) | Female # 30-34 years (429,453). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Illinois population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Illinois is shown in the following column.
• Population (Female): The female population in the Illinois is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Illinois for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Gender. You can refer the same here

Comprehensive dataset of 21 Student career counseling offices in Illinois, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

These data are appropriate for use in local and regional thematic analysis. The data are not appropriate as a geodetic, legal or engineering base. The data set was not and is not intended as a substitute for surveyed locations, such as can be determined by a registered Public Land Surveyor. Although useful in a GIS as a reference base layer for maps, the data set has no legal basis in the definition of boundaries or property lines.

Comprehensive dataset of 239 Education in Illinois, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 34 Amphitheaters in Illinois, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 6,489 Manufacturers in Illinois, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Coups d'Ètat are important events in the life of a country. They constitute an important subset of irregular transfers of political power that can have significant and enduring consequences for national well-being. There are only a limited number of datasets available to study these events (Powell and Thyne 2011, Marshall and Marshall 2019). Seeking to facilitate research on post-WWII coups by compiling a more comprehensive list and categorization of these events, the Cline Center for Advanced Social Research (previously the Cline Center for Democracy) initiated the Coup d’État Project as part of its Societal Infrastructures and Development (SID) project. More specifically, this dataset identifies the outcomes of coup events (i.e., realized, unrealized, or conspiracy) the type of actor(s) who initiated the coup (i.e., military, rebels, etc.), as well as the fate of the deposed leader. Version 2.1.3 adds 19 additional coup events to the data set, corrects the date of a coup in Tunisia, and reclassifies an attempted coup in Brazil in December 2022 to a conspiracy. Version 2.1.2 added 6 additional coup events that occurred in 2022 and updated the coding of an attempted coup event in Kazakhstan in January 2022. Version 2.1.1 corrected a mistake in version 2.1.0, where the designation of “dissident coup” had been dropped in error for coup_id: 00201062021. Version 2.1.1 fixed this omission by marking the case as both a dissident coup and an auto-coup. Version 2.1.0 added 36 cases to the data set and removed two cases from the v2.0.0 data. This update also added actor coding for 46 coup events and added executive outcomes to 18 events from version 2.0.0. A few other changes were made to correct inconsistencies in the coup ID variable and the date of the event. Version 2.0.0 improved several aspects of the previous version (v1.0.0) and incorporated additional source material to include: • Reconciling missing event data • Removing events with irreconcilable event dates • Removing events with insufficient sourcing (each event needs at least two sources) • Removing events that were inaccurately coded as coup events • Removing variables that fell below the threshold of inter-coder reliability required by the project • Removing the spreadsheet ‘CoupInventory.xls’ because of inadequate attribution and citations in the event summaries • Extending the period covered from 1945-2005 to 1945-2019 • Adding events from Powell and Thyne’s Coup Data (Powell and Thyne, 2011)
Items in this Dataset 1. Cline Center Coup d'État Codebook v.2.1.3 Codebook.pdf - This 15-page document describes the Cline Center Coup d’État Project dataset. The first section of this codebook provides a summary of the different versions of the data. The second section provides a succinct definition of a coup d’état used by the Coup d'État Project and an overview of the categories used to differentiate the wide array of events that meet the project's definition. It also defines coup outcomes. The third section describes the methodology used to produce the data. Revised February 2024 2. Coup Data v2.1.3.csv - This CSV (Comma Separated Values) file contains all of the coup event data from the Cline Center Coup d’État Project. It contains 29 variables and 1000 observations. Revised February 2024 3. Source Document v2.1.3.pdf - This 325-page document provides the sources used for each of the coup events identified in this dataset. Please use the value in the coup_id variable to identify the sources used to identify that particular event. Revised February 2024 4. README.md - This file contains useful information for the user about the dataset. It is a text file written in markdown language. Revised February 2024
Citation Guidelines 1. To cite the codebook (or any other documentation associated with the Cline Center Coup d’État Project Dataset) please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Scott Althaus. 2024. “Cline Center Coup d’État Project Dataset Codebook”. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7 2. To cite data from the Cline Center Coup d’État Project Dataset please use the following citation (filling in the correct date of access): Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, Jonathan Bonaguro, and Emilio Soto. 2024. Cline Center Coup d’État Project Dataset. Cline Center for Advanced Social Research. V.2.1.3. February 27. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-9651987_V7

About this dataset

Context

The dataset tabulates the Illinois population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Illinois. The dataset can be utilized to understand the population distribution of Illinois by age. For example, using this dataset, we can identify the largest age group in Illinois.

Key observations

The largest age group in Illinois was for the group of age 30 to 34 years years with a population of 866,468 (6.83%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Illinois was the 80 to 84 years years with a population of 238,424 (1.88%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Illinois is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Illinois total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Age. You can refer the same here

Comprehensive dataset of 52 Stages in Illinois, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 70 Apartments in Illinois, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Cline Center Historical Phoenix Event Data covers the period 1945-2019 and includes 8.2 million events extracted from 21.2 million news stories. This data was produced using the state-of-the-art PETRARCH-2 software to analyze content from the New York Times (1945-2018), the BBC Monitoring's Summary of World Broadcasts (1979-2019), the Wall Street Journal (1945-2005), and the Central Intelligence Agency’s Foreign Broadcast Information Service (1995-2004). It documents the agents, locations, and issues at stake in a wide variety of conflict, cooperation and communicative events in the Conflict and Mediation Event Observations (CAMEO) ontology. The Cline Center produced these data with the generous support of Linowes Fellow and Faculty Affiliate Prof. Dov Cohen and help from our academic and private sector collaborators in the Open Event Data Alliance (OEDA). For details on the CAMEO framework, see: Schrodt, Philip A., Omür Yilmaz, Deborah J. Gerner, and Dennis Hermreck. "The CAMEO (conflict and mediation event observations) actor coding framework." In 2008 Annual Meeting of the International Studies Association. 2008. http://eventdata.parusanalytics.com/papers.dir/APSA.2005.pdf Gerner, D.J., Schrodt, P.A. and Yilmaz, O., 2012. Conflict and mediation event observations (CAMEO) Codebook. http://eventdata.parusanalytics.com/cameo.dir/CAMEO.Ethnic.Groups.zip For more information about PETRARCH and OEDA, see: http://openeventdata.org/

This dataset was developed as part of a study that assessed data reuse. Through bibliometric analysis, corresponding authors of highly cited papers published in 2015 at the University of Illinois at Urbana-Champaign in nine STEM disciplines were identified and then surveyed to determine if data were generated for their article and their knowledge of reuse by other researchers. Second, the corresponding authors who cited those 2015 articles were identified and surveyed to ascertain whether they reused data from the original article and how that data was obtained. The project goal was to better understand data reuse in practice and to explore if research data from an initial publication was reused in subsequent publications.

This data comes from a scoping review associated with the project called Reducing the Inadvertent Spread of Retracted Science. The data summarizes the fields that have been explored by existing research on retraction, a list of studies comparing retraction in different fields, and a list of studies focused on retraction of COVID-19 articles.