- Research Nodes
- Demonstrator Projects
- Sustainability Projects
- Community Funded Projects
- Research Networks and Partnerships
- Tools and Downloads
The overall objective is to realise the ESRC vision of e-science enabling cutting edge methodological developments to help quantitative researchers do new and better research and to provide learning pathways to bring these cutting edge developments into the working practices of quantitative social sciences.
To this end we will:
Build a stronger network between the DSR and NCRM programmes
The new node sits at the intersection of the Digital Social Research (DSR) programme and the ESRC National Centre for Research methods (NCRM), with the Southampton e-Science team closely involved in DSR and the Bristol team heavily involved in the NCRM. It will act to bring the e-science and quantitative social science communities closer by developing activities which combine expertise and capability in each and by actively constructing networks that facilitate flow between the two sister programmes.
Produce tools that enhance productivity across the entire research process
The node addresses the lifecycle of quantitative research by providing tools to facilitate dataset discovery, combination, analysis, interpretation, visualisation, documenting the whole process, paper authoring and publication of results data and
Use these tools to progress 5 important quantitative social science applications
Applications in the areas of social segregation, child development, social networks, sample size calculations and handling missing data will inform and showcase the sets of tools we provide and develop.
Not re-invent the wheel, re-use what is good
We will place these tools in a framework that allows interoperability with existing tools and only implement new tools where there is a clearly identified user demand for the functionality. The framework will use web standards and favour simplicity and ease of reuse.
Produce tools, services and materials that cater for a diversity of users
We will develop a new type of statistical software environment targeted at a diversity of users that will provide the platform for a new generation of quantitative social scientists from the novice consumer to the highly experienced developer.
Produce tools that support collaborative research across different packages. Often collaborating researchers use different software packages. We will explore providing tools for interoperability between software packages that allow users to share and work on common research artifacts without having to learn each other’s software packages.
Produce tools for documenting the research process in a form suitable for sharing
We will create tools for packaging the artifacts of the research process (data, tables, models, graphs, scripts) into executable notebooks. Executable notebooks combine the narrative and expository advantages of conventional technical papers and the interactive and experimental advantages of software.
Produce tools for sharing results and techniques across the broad community
We will facilitate and encourage sharing of data, tools, methods and expertise by providing tools that make that sharing possible and a social networking environment which is highly sympathetic to researchers’ needs and which encourages sharing. These tools will have sophisticated tagging and searching facilities to allow users to find the content they need. In particular we will create social networking tools for sharing executable workbooks.
Use these tools to showcase and disseminate NCRM methodological developments
Our tools will support interoperability between the different software packages used by the NCRM quantitative nodes and can act as a dissemination device for NCRM developments.
Use these tools to showcase and disseminate DSR e-social science developments
We will work with the DSR nodes and the NCeSS Infrastructure Project to ensure that the node engages with emerging results, needs, tools and practices of e-Social Science and helps bring these developments to the wider audience.
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