Related Experiment Video
Updated: Jun 10, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure
Guy C Warner1, Jesse M Blum, Simon B Jones
1Department of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, UK. gcw@cs.stir.ac.uk
Abstract:
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.
Related Concept Videos
Statistical Package for the Social Sciences (SPSS)
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
GIS Software, Hardware, and Sources of GIS Data
Statistical Analysis System (SAS)
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Applications of GIS: Disaster Management and Emergency Response
Statistical Software for Data Analysis and Clinical Trials
Data Reporting and Recording

