Interactive tag maps and tag clouds for the multiscale exploration of large spatio-temporal datasets

'Tag clouds' and 'tag maps' are introduced to represent geographically referenced text. In combination, these aspatial and spatial views are used to explore a large structured spatio-temporal data set by providing overviews and filtering by text and geography. Prototypes are implemented using freely available technologies including Google Earth and Yahoo! 's Tag Map applet. The interactive tag map and tag cloud techniques and the rapid prototyping method used are informally evaluated through successes and limitations encountered. Preliminary evaluation suggests that the techniques may be useful for generating insights when visualizing large data sets containing geo-referenced text strings. The rapid prototyping approach enabled the technique to be developed and evaluated, leading to geovisualization through which a number of ideas were generated. Limitations of this approach are reflected upon. Tag placement, generalisation and prominence at different scales are issues which have come to light in this study that warrant further work

Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here

Informing Non-Response Bias Model Creation in Social Surveys with Visualisation

Through an ongoing process of co-design and co-discovery we are developing and using visualization to explore large amounts of auxiliary data from unfamiliar sources to understand non-response bias in social surveys. We present auxiliary data in their geographical contexts and show how this can complement traditional data analysis and provide a more comprehensive understanding of the data. This is helping select variables for non-response modelling. These processes are not just limited to non-response analysis, but have potential to be used in wider quantitative analysis in social science

Supporting Theoretically-grounded Model Building in the Social Sciences through Interactive Visualisation

The primary purpose for which statistical models are employed in the social sciences is to understand and explain phenomena occurring in the world around us. In order to be scientifically valid and actionable, the construction of such models need to be strongly informed by theory. To accomplish this, there is a need for methodologies that can enable scientists to utilise their domain knowledge effectively even in the absence of strong a priori hypotheses or whilst dealing with complex datasets containing hundreds of variables and leading to large numbers of potential models. In this paper, we describe enhanced model building processes in which we use interactive visualisations as the underlying mechanism to facilitate the construction and documentation of theory-driven models. We report our observations from a collaborative project involving social and computer scientists, and identify key roles for visualisation to support model building within the context of social science. We describe a suite of techniques to facilitate the exploration of statistical summaries of input variables, to compare the quality of alternative models, and to keep track of the model-building process. We demonstrate how these techniques operate in coordination to allow social scientists to efficiently generate models that are tightly underpinned by domain specific theory

Enhancing a Social Science Model-building Workflow with Interactive Visualisation

Models can help scientists study and understand phenomena. Such models need to be informed by theory. We report on the early stages of our ongoing study in which we use interactive visualisation to help improve the construction of theory-driven models, by facilitating the exploration of statistical summaries of input variables, compare the quality of alternative models and keep track of the model-building process. Later work will investigate whether machine-learning techniques can be incorporated without compromising the models' theoretical bases

A and B antigen levels acquired by group O donor-derived erythrocytes following ABO-non-identical transfusion or minor ABO-incompatible haematopoietic stem cell transplantation

BACKGROUND AND OBJECTIVES: ABO-incompatible haematopoietic stem cell transplantation (HSCT) presents a challenge to blood component transfusion. The aim of this study was to investigate the weak blood group A or B antigen expression by donor-derived group O red blood cells (RBC) observed following transfusion or minor ABO-incompatible HSCT. In addition, in vitro experiments were performed to elucidate possible mechanisms underlying this phenomenon.MATERIALS AND METHODS: A sensitive flow cytometry assay for the semi-quantification of RBC A/B antigen levels was used to assess patient samples and evaluate in vitro experiments.RESULTS: Analysis of blood samples from patients, originally typed as A, B and AB but recently transplanted or transfused with cells from group O donors, revealed the A antigen expression on donor-derived RBC, ranging from very low levels in non-secretor individuals to almost subgroup Ax -like profiles in group A secretors. The B antigen expression was less readily detectable. In vitro experiments, in which group O donor RBC were incubated with (i) group A/B secretor/non-secretor donor plasma or (ii) group A/B donor RBC in the absence of plasma, supported the proposed adsorption of A/B antigen-bearing glycolipids from secretor plasma but also indicated a secretor-independent mechanism for A/B antigen acquisition as well as direct cell-to-cell transfer of ABO antigens.CONCLUSION: The in vivo conversion of donor-derived blood group O RBC to ABO subgroup-like RBC after transfusion or minor ABO-incompatible HSCT raises the question of appropriate component selection. Based on these data, AB plasma should be transfused following ABO-incompatible HSCT

An extensible framework for provenance in human terrain visual analytics

We describe and demonstrate an extensible framework that supports data exploration and provenance in the context of Human Terrain Analysis (HTA). Working closely with defence analysts we extract requirements and a list of features that characterise data analysed at the end of the HTA chain. From these, we select an appropriate non-classified data source with analogous features, and model it as a set of facets. We develop ProveML, an XML-based extension of the Open Provenance Model, using these facets and augment it with the structures necessary to record the provenance of data, analytical process and interpretations. Through an iterative process, we develop and refine a prototype system for Human Terrain Visual Analytics (HTVA), and demonstrate means of storing, browsing and recalling analytical provenance and process through analytic bookmarks in ProveML. We show how these bookmarks can be combined to form narratives that link back to the live data. Throughout the process, we demonstrate that through structured workshops, rapid prototyping and structured communication with intelligence analysts we are able to establish requirements, and design schema, techniques and tools that meet the requirements of the intelligence community. We use the needs and reactions of defence analysts in defining and steering the methods to validate the framework