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Introduction Pyramid Exercise |
Visualisation in the Social Sciences WorkshopTowards a Research Agenda for Social Science VisualisationTABLE 3: Sixty-seven issues identified by the twenty-four participants | |
A | Research into user experiences, appropriations… | |
A | Support to encourage the development of visualisation in qualitative social science. | |
A | Research into the visualisation of text, | |
A | Research into the potential of visualisation in linking qualitative and quantitative research | |
A | Communication: clear identification of visualisation approach and communication of techniques | |
A | Development and incorporation of techniques at the start of research projects | |
A | Innovative use of technology | |
A | Repository for visualisation examples and tools. | |
A | Promoting inter disciplinary communication | |
A | Evaluation of the effectiveness of visualisation | |
A | Storyboarding websites | |
A | Organizing web data without anarchy | |
A | Non hierarchical data coding | |
A | Problem visualisation tools | |
A | Examples of good and bad practice | |
A | Visualisation of highly multivariate data | |
A | Schematic visualisation: one ink colour and so on | |
A | Chernoff face research centre(?) | |
A | Fund example projects in history and sociology to demonstrate actual usefulness | |
A | Name and shame examples of visualisation | |
B | 'Lightweight' mapping | |
B | Visualisation of spatial statistics | |
B | Visualisation of networks, both physical and conceptual especially flow data, text, etc | |
B | Visualisation of spatially varying parameters | |
B | Visualisation of large interaction matrices | |
B | Visualisation of hypervariate spatial data | |
B | Persuade the rest of social science to use visualisation and not Excel | |
B | Collaborative visualisation | |
B | Visualisation on the web | |
B | Support for navigation through large multi-dimensional data sets | |
B | Evaluation of visualisation tools and techniques | |
B | The development and assessment of collaborative visualisation techniques | |
B | Making visualisation technologies more accessible to the social sciences | |
B | Assessment and evaluation of the effectiveness of the visualisation process | |
B | Visualisation of qualitative information | |
B | Techniques for the visualisation of temporal aspects of spatial data | |
B | Perceptual aspects of visualisation | |
B | Network visualisation | |
B | Dynamic visualisation of social phenomena | |
B | Development of customized visualisation tools for specific groups of end users | |
B | Tools for public or collaborative visualisation | |
B | Assessing the effectiveness of visualisation methods | |
B | Visualisation of complex multivariate data sets | |
C | Experimental methods to assess the effectiveness of visualisation | |
C | Development of effective strategies for visualisation of multi-node flows | |
C | Generic and general methods for structuring, linking and navigating images and texts | |
C | Experimental evaluation of how people use visualisation | |
C | Case studies development of use of tools in different social sciences | |
C | Postgraduate training courses in visualisation | |
C | Use of images as qualitative data in research | |
C | Visualising networks in qualitative data (e.g. NUDIST) | |
C | Evaluative work in the use of visualisation | |
C | Trying to spread visualisation wider within the social sciences | |
C | Visualisation officer for social sciences? | |
C | Person flow visualisation | |
C | The role of VR is visualising spatial data | |
C | Visualisation of individual level population dynamics | |
C | Visualisation of qualitative data | |
C | 'Collapsing the MacEachren cube' | |
C | Development of methods to visualize hypervariate data | |
C | Development of ways to assess visualisation methods | |
C | Development of local statistics approach | |
C | Development of accessible tools for social science visualisation | |
C | Classification of psychological concepts in health care research | |
C | Information science tools in visualisation to support health care assessment programmes. | |
C | Research into existing manual/electronic forms of data capture |
Graphics Multimedia Virtual Environments Visualisation Contents