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Combining formal and exploratory methods for evaluation of an exploratory geovisualization application in a low-cost usability experiment
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
2007 (English)In: Cartography and Geographic Information Science, ISSN 1523-0406, Vol. 34, no 1, 29-45 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a joined formal and exploratory usability evaluation of a geovisualization tool for emergency response data. The first objective of the evaluation, which is addressed by a formal usability test, is to evaluate the performance of the test participants on pre-defined exploration tasks. The second objective is to attempt to better understand how the participants explore the spatial dataset. This objective is addressed in the exploratory usability part of the experiment, where participants are given free hand to perform exploration in any way they want. The study introduces a low-cost methodology for performing usability evaluation, which uses simple and inexpensive methods for data collection and analysis, yet proves to be adequate to identify potentials and problems of the tool.

Place, publisher, year, edition, pages
2007. Vol. 34, no 1, 29-45 p.
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-5509DOI: 10.1559/152304007780279069OAI: oai:DiVA.org:kth-5509DiVA: diva2:9899
Note
QC 20110117 Tidigare titel: A low-cost usability evaluation of a visual data mining system for geospatial data. Uppdaterad från submitted till published(20110117) Available from: 2006-03-21 Created: 2006-03-21 Last updated: 2011-01-17Bibliographically approved
In thesis
1. Data mining of geospatial data: combining visual and automatic methods
Open this publication in new window or tab >>Data mining of geospatial data: combining visual and automatic methods
2006 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting this information and knowledge is data mining. Knowledge discovery is performed by applying automatic algorithms which recognise patterns in the data.

Classical data mining algorithms assume that data are independently generated and identically distributed. Geospatial data are multidimensional, spatially autocorrelated and heterogeneous. These properties make classical data mining algorithms inappropriate for geospatial data, as their basic assumptions cease to be valid. Extracting knowledge from geospatial data therefore requires special approaches. One way to do that is to use visual data mining, where the data is presented in visual form for a human to perform the pattern recognition. When visual mining is applied to geospatial data, it is part of the discipline called exploratory geovisualisation.

Both automatic and visual data mining have their respective advantages. Computers can treat large amounts of data much faster than humans, while humans are able to recognise objects and visually explore data much more effectively than computers. A combination of visual and automatic data mining draws together human cognitive skills and computer efficiency and permits faster and more efficient knowledge discovery.

This thesis investigates if a combination of visual and automatic data mining is useful for exploration of geospatial data. Three case studies illustrate three different combinations of methods. Hierarchical clustering is combined with visual data mining for exploration of geographical metadata in the first case study. The second case study presents an attempt to explore an environmental dataset by a combination of visual mining and a Self-Organising Map. Spatial pre-processing and visual data mining methods were used in the third case study for emergency response data.

Contemporary system design methods involve user participation at all stages. These methods originated in the field of Human-Computer Interaction, but have been adapted for the geovisualisation issues related to spatial problem solving. Attention to user-centred design was present in all three case studies, but the principles were fully followed only for the third case study, where a usability assessment was performed using a combination of a formal evaluation and exploratory usability.

Place, publisher, year, edition, pages
Stockholm: KTH, 2006. x, 91 p.
Series
Trita-SOM , ISSN 1653-6126 ; 06:01
Keyword
geographic information science, geoinformatics, geovisualisation, spatial data mining, visual data mining, usability evaluation
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:kth:diva-3892 (URN)91-7178-297-4 (ISBN)
Public defence
2006-04-07, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00
Opponent
Supervisors
Note
QC 20110118Available from: 2006-03-21 Created: 2006-03-21 Last updated: 2011-01-18Bibliographically approved

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