Supporting analytical reasoning: A study from the automotive industry
2016 (English)In: Human Interface and the Management of Information: Applications and Services: 18th International Conference, HCI International 2016 Toronto, Canada, July 17-22, 2016. Proceedings, Part II / [ed] Sakae Yamamoto, Springer, 2016, 20-31 p.Conference paper (Refereed)
In the era of big data, it is imperative to assist the human analyst in the endeavor to find solutions to ill-defined problems, i.e. to “detect the expected and discover the unexpected” (Yi et al., 2008). To their aid, a plethora of analysis support systems is available to the analysts. However, these support systems often lack visual and interactive features, leaving the analysts with no opportunity to guide, influence and even understand the automatic reasoning performed and the data used. Yet, to be able to appropriately support the analysts in their sense-making process, we must look at this process more closely. In this paper, we present the results from interviews performed together with data analysts from the automotive industry where we have investigated how they handle the data, analyze it and make decisions based on the data, outlining directions for the development of analytical support systems within the area.
Place, publisher, year, edition, pages
Springer, 2016. 20-31 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 9735
analytical reasoning, sense-making, visual analytics, truck data analysis, big data
Human Computer Interaction
Research subject Technology
IdentifiersURN: urn:nbn:se:his:diva-12801DOI: 10.1007/978-3-319-40397-7_3ScopusID: 2-s2.0-84978877445ISBN: 978-3-319-40396-0ISBN: 978-3-319-40397-7OAI: oai:DiVA.org:his-12801DiVA: diva2:954235
18th International Conference on Human Interface and the Management of Information (HCI International 2016), Toronto, Canada, July 17-22, 2016.
ProjectsBIDAF - A Big Data Analytics Framework for a Smart Society
FunderKnowledge Foundation, BIDAF 2014/32