A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure

2010 ◽  
Vol 368 (1925) ◽  
pp. 3859-3873 ◽  
Author(s):  
Guy C. Warner ◽  
Jesse M. Blum ◽  
Simon B. Jones ◽  
Paul S. Lambert ◽  
Kenneth J. Turner ◽  
...  
Keyword(s):  
Social Science ◽  
Data Fusion ◽  
Data Management ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Project Approach ◽  
Computing Power ◽  
Social Science Data ◽  
Using Data

The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analytical methodologies, such as microsimulation, and increases in computing power. These rich resources do, however, bring with them substantial challenges associated with organizing and using data. These processes are often referred to as ‘data management’. The Data Management through e-Social Science (DAMES) project is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data-fusion process that is central to the project approach. It covers: the background and requirements for provision of resources by DAMES; the use of grid technologies to provide easy-to-use tools and user front-ends for several common social science data-management tasks such as data fusion; the approach taken to solve problems related to data resources and metadata relevant to social science applications; and the implementation of the architecture that has been designed to achieve this infrastructure.

scholarly journals Uncomfortable Decisions

2022 ◽  
Author(s):  
Paul Bloom ◽  
Laurie Paul
Keyword(s):  
Decision Making ◽  
Social Science ◽  
Career Change ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Decision Making Processes ◽  
Social Science Data ◽  
Personal Decision ◽  
Algorithmic Process

Some decision-making processes are uncomfortable. Many of us do not like to make significant decisions, such as whether to have a child, solely based on social science research. We do not like to choose randomly, even in cases where flipping a coin is plainly the wisest choice. We are often reluctant to defer to another person, even if we believe that the other person is wiser, and have similar reservations about appealing to powerful algorithms. And, while we are comfortable with considering and weighing different options, there is something strange about deciding solely on a purely algorithmic process, even one that takes place in our own heads.What is the source of our discomfort? We do not present a decisive theory here—and, indeed, the authors have clashing views over some of these issues—but we lay out the arguments for two (consistent) explanations. The first is that such impersonal decision-making processes are felt to be a threat to our autonomy. In all of the examples above, it is not you who is making the decision, it is someone or something else. This is to be contrasted with personal decision-making, where, to put it colloquially, you “own” your decision, though of course you may be informed by social science data, recommendations of others, and so on. A second possibility is that such impersonal decision-making processes are not seen as authentic, where authentic decision making is one in which you intentionally and knowledgably choose an option in a way that is “true to yourself.” Such decision making can be particularly important in contexts where one is making a life-changing decision of great import, such as the choice to emigrate, start a family, or embark on a major career change.

scholarly journals Metadata Creation, Transformation and Discovery for Social Science Data Management: The DAMES Project Infrastructure

2010 ◽  
Vol 33 (1) ◽  
pp. 23 ◽  
Author(s):  
Jesse M. Blum ◽  
Guy C. Warner ◽  
Simon B. Jones ◽  
Paul S. Lambert ◽  
Alison S. F. Dawson
Keyword(s):  
Social Science ◽  
Data Management ◽  
Science Data ◽  
Social Science Data

Metadata Creation, Transformation and Discovery for Social Science Data Management: The DAMES Project Infrastructure

Ethical Data Mining and Social Science Data Exploration and Description

2013 ◽  
pp. 22-39
Author(s):  
Arabi U.
Keyword(s):  
Data Mining ◽  
Social Science ◽  
Teen Pregnancy ◽  
Social Indicators ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Technology Innovations ◽  
The Status ◽  
The Impact

As data mining is the process of discovering significant, valuable, and interesting relationships in large and complex volumes of data (especially in data-enriched areas of socio-economic domains and in this socio-economic aspect of a society), data mining applications essentially act as effective instruments for providing support for measuring socio-economic pattern in a society. Although social and ethical matters are nowadays concerns to the society of which people are the only elements, in the days of technology innovations, computers are being manipulated with programs to act more like people, and eventually several social and ethical matters come into focus related to computer programming, or artificial intelligence. Researchers from nearly every social science discipline have found themselves in the position of simultaneously evaluating many questions, testing many hypotheses, or comparing many point estimates. In program evaluation, this arises, for instance, when comparing the impact of several different policy interventions; comparing the status of social indicators like test scores, poverty rates, teen pregnancy rates etc. across multiple schools, states, or countries; examining whether treatment effects vary meaningfully across different sub groups of the population; or examining the impact of a program on many different outcomes. Hence, the relevance of positioning of this chapter in a book of ethical data mining applications for socio-economic development of a community, society, or country fits well as the ethical data mining in social science research is crucial as such data information is highly useful in testing many of the hypotheses of economic or socio-economic in nature.

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