Review of An Introduction to Data Management in the Behavioral and Social Sciences.

1971 ◽  
Vol 16 (10) ◽  
pp. 670-670
Author(s):  
B. J. WINER
Keyword(s):  
Social Sciences ◽  
Data Management

An Introduction to Data Management in the Behavioral and Social Sciences.

1972 ◽  
Vol 135 (2) ◽  
pp. 283
Author(s):  
H. Goldstein ◽  
S. Blackman ◽  
K. M. Goldstein
Keyword(s):  
Social Sciences ◽  
Data Management

scholarly journals A Report of Data-Intensive Capability, Institutional Support, and Data Management Practices in Social Sciences

2016 ◽  
Vol 11 (1) ◽  
pp. 156 ◽  
Author(s):  
Wei Jeng ◽  
Liz Lyon
Keyword(s):  
Social Sciences ◽  
Data Management ◽  
Data Science ◽  
Management Practices ◽  
Information Science ◽  
Institutional Support ◽  
Current Data ◽  
Management Support ◽  
Model Framework ◽  
Data Intensive

We report on a case study which examines the social science community’s capability and institutional support for data management. Fourteen researchers were invited for an in-depth qualitative survey between June 2014 and October 2015. We modify and adopt the Community Capability Model Framework (CCMF) profile tool to ask these scholars to self-assess their current data practices and whether their academic environment provides enough supportive infrastructure for data related activities. The exemplar disciplines in this report include anthropology, political sciences, and library and information science. Our findings deepen our understanding of social disciplines and identify capabilities that are well developed and those that are poorly developed. The participants reported that their institutions have made relatively slow progress on economic supports and data science training courses, but acknowledged that they are well informed and trained for participants’ privacy protection. The result confirms a prior observation from previous literature that social scientists are concerned with ethical perspectives but lack technical training and support. The results also demonstrate intra- and inter-disciplinary commonalities and differences in researcher perceptions of data-intensive capability, and highlight potential opportunities for the development and delivery of new and impactful research data management support services to social sciences researchers and faculty. 

An Introduction to Data Management in the Behavioral and Social Sciences.

1972 ◽  
Vol 1 (6) ◽  
pp. 522
Author(s):  
Andy B. Anderson ◽  
Sheldon Blackman ◽  
Kenneth M. Goldstein ◽  
William W. Cooley ◽  
Paul R. Lohnes
Keyword(s):  
Social Sciences ◽  
Data Management

scholarly journals Research Data Management and Data Sharing among Research Scholars of Life Sciences and Social Sciences

2019 ◽  
Vol 39 (06) ◽  
pp. 290-299
Author(s):  
Naushad Ali PM ◽  
Sidra Saeed
Keyword(s):  
Social Sciences ◽  
Data Management ◽  
Data Sharing ◽  
Life Sciences ◽  
Scientific Progress ◽  
Research Data ◽  
Key Factors ◽  
Research Data Management ◽  
Share Data

This study investigates perception of research scholars towards research data management and sharing. A survey was conducted among research scholars from Faculty of Life Sciences and Social Sciences, Aligarh Muslim University (AMU). In total, 352 participants filled out the questionnaire. The study shows that research scholars ofFaculty of Social Sciences are more willing to share their research data as compared to Research Scholars of Life Sciences. Contributing to scientific progress and increasing research citations and visibility were the key factors that motivated researchers to share data. However, confidentiality and data misuse were the main concerns among those who were unwilling to share. Finally, some recommendations to improve the of data management and sharing practices are presented.

scholarly journals An Exploratory Analysis of Social Science Graduate Education in Data Management and Data Sharing

2020 ◽  
Vol 15 (1) ◽  
pp. 18
Author(s):  
Ashley Doonan ◽  
Dharma Akmon ◽  
Evan Cosby
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Data Management ◽  
Graduate Education ◽  
Data Sharing ◽  
Graduate Programs ◽  
Formal Training ◽  
The Social ◽  
Syllabus Analysis ◽  
Science Disciplines

Effective data management and data sharing are crucial components of the research lifecycle, yet evidence suggests that many social science graduate programs are not providing training in these areas. The current exploratory study assesses how U.S. masters and doctoral programs in the social sciences include formal, non-formal, and informal training in data management and sharing. We conducted a survey of 150 graduate programs across six social science disciplines, and used a mix of closed and open-ended questions focused on the extent to which programs provide such training and exposure. Results from our survey suggested a deficit of formal training in both data management and data sharing, limited non-formal training, and cursory informal exposure to these topics. Utilizing the results of our survey, we conducted a syllabus analysis to further explore the formal and non-formal content of graduate programs beyond self-report. Our syllabus analysis drew from an expanded seven social science disciplines for a total of 140 programs. The syllabus analysis supported our prior findings that formal and non-formal inclusion of data management and data sharing training is not common practice. Overall, in both the survey and syllabi study we found a lack of both formal and non-formal training on data management and data sharing. Our findings have implications for data repository staff and data service professionals as they consider their methods for encouraging data sharing and prepare for the needs of data depositors. These results can also inform the development and structuring of graduate education in the social sciences, so that researchers are trained early in data management and sharing skills and are able to benefit from making their data available as early in their careers as possible.

Building Socio-technical Systems to Support Data Management and Digital Scholarship in the Social Sciences

2019 ◽  
pp. 31-57
Author(s):  
Plato L. Smith ◽  
Crystal Felima ◽  
Fletcher Durant ◽  
David Van Kleeck ◽  
Hélène Huet ◽  
...  
Keyword(s):  
Social Sciences ◽  
Data Management ◽  
Digital Scholarship ◽  
The Social ◽  
Technical Systems
Sign in / Sign up

Export Citation Format

Share Document