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Supporting Analytical Reasoning

A Study from the Automotive Industry
  • Tove HelldinEmail author
  • Maria Riveiro
  • Sepideh Pashami
  • Göran Falkman
  • Stefan Byttner
  • Slawomir Nowaczyk
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9735)

Abstract

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” [23]. 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.

Keywords

Analytical reasoning Sense-making Visual analytics Truck data analysis Big data 

Notes

Acknowledgment

This research has been conducted within the A Big Data Analytics Framework for a Smart Society (BIDAF 2014/32) project, supported by the Swedish Knowledge Foundation. We would like to thank the study participants for their valuable feedback.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Tove Helldin
    • 1
    Email author
  • Maria Riveiro
    • 1
  • Sepideh Pashami
    • 2
  • Göran Falkman
    • 1
  • Stefan Byttner
    • 2
  • Slawomir Nowaczyk
    • 2
  1. 1.University of SkövdeSkövdeSweden
  2. 2.Halmstad UniversityHalmstadSweden

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