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  • 1.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Visual Data Analysis2019In: Data science in Practice / [ed] A. Said, & V. Torra, Springer, 2019, p. 133-155Chapter in book (Refereed)
    Abstract [en]

    Data Science offers a set of powerful approaches for making new discoveries from large and complex data sets. It combines aspects of mathematics, statistics, machine learning, etc. to turn vast amounts of data into new insights and knowledge. However, the sole use of automatic data science techniques for large amounts of complex data limits the human user’s possibilities in the discovery process, since the user is estranged from the process of data exploration. This chapter describes the importance of Information Visualization (InfoVis) and visual analytics (VA) within data science and how interactive visualization can be used to support analysis and decision-making, empowering and complementing data science methods. Moreover, we review perceptual and cognitive aspects, together with design and evaluation methodologies for InfoVis and VA.

  • 2.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Identifying Root Cause and Derived Effects in Causal Relationships2017In: Human Interface and the Management of Information: Information, Knowledge and Interaction Design: 19th International Conference, HCI International 2017, Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part I / [ed] Sakae Yamamoto, Springer , 2017, p. 22-34Conference paper (Refereed)
    Abstract [en]

    This paper focuses on identifying factors that influence the process of finding a root cause and a derived effect in causal node-link graphs with associated strength and significance depictions. We discuss in detail the factors that seem to be involved in identifying a global cause and effect based on the analysis of the results of an online user study with 44 participants, who used both sequential and non-sequential graph layouts. In summary, the results show that participants show geodesic-path tendencies when selecting causes and derived effects, and that context matters, i.e., participant’s own beliefs, experiences and knowledge might influence graph interpretation.

  • 3.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Understanding Indirect Causal Relationships in Node-Link Graphs2017In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, no 3, p. 411-421Article in journal (Refereed)
    Abstract [en]

    To find correlations and cause and effect relationships in multivariate data sets is central in many data analysis problems. A common way of representing causal relations among variables is to use node-link diagrams, where nodes depict variables and edges show relationships between them. When performing a causal analysis, analysts may be biased by the position of collected evidences, especially when they are at the top of a list. This is of crucial importance since finding a root cause or a derived effect, and searching for causal chains of inferences are essential analytic tasks when investigating causal relationships. In this paper, we examine whether sequential ordering influences understanding of indirect causal relationships and whether it improves readability of multi-attribute causal diagrams. Moreover, we see how people reason to identify a root cause or a derived effect. The results of our design study show that sequential ordering does not play a crucial role when analyzing causal relationships, but many connections from/to a variable and higher strength/certainty values may influence the process of finding a root cause and a derived effect.

  • 4.
    Bae, Juhee
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Ventocilla, Elio
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Evaluating Multi-Attributes on Cause and Effect Relationship Visualization2017In: Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017): Volumne 3: IVAPP / [ed] Alexandru Telea, Jose Braz, Lars Linsen, SciTePress , 2017, p. 64-74Conference paper (Refereed)
    Abstract [en]

    This paper presents findings about visual representations of cause and effect relationship's direction, strength, and uncertainty based on an online user study. While previous researches focus on accuracy and few attributes, our empirical user study examines accuracy and the subjective ratings on three different attributes of a cause and effect relationship edge. The cause and effect direction was depicted by arrows and tapered lines; causal strength by hue, width, and a numeric value; and certainty by granularity, brightness, fuzziness, and a numeric value. Our findings point out that both arrows and tapered cues work well to represent causal direction. Depictions with width showed higher conjunct accuracy and were more preferred than that with hue. Depictions with brightness and fuzziness showed higher accuracy and were marked more understandable than granularity. In general, depictions with hue and granularity performed less accurately and were not preferred compared to the ones with numbers or with width and brightness.

    Download full text (pdf)
    FULLTEXT01
  • 5.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Dahlbom, Anders
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lebram, Mikael
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Transparency of military threat evaluation through visualizing uncertainty and system rationale2013In: Engineering Psychology and Cognitive Ergonomics: Applications and Services / [ed] Don Harris, Springer, 2013, p. 263-272Conference paper (Refereed)
    Abstract [en]

    Threat evaluation (TE) is concerned with determining the intent, capability and opportunity of detected targets. To their aid, military operators use support systems that analyse incoming data and make inferences based on the active evaluation framework. Several interface and interaction guidelines have been proposed for the implementation of TE systems; however there is a lack of research regarding how to make these systems transparent to their operators. This paper presents the results from interviews conducted with TE operators focusing on the need for and possibilities of improving the transparency of TE systems through the visualization of uncertainty and the presentation of the system rationale. © 2013 Springer-Verlag Berlin Heidelberg.

  • 6.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Davidsson, Staffan
    Volvo Car Corporation, Gothenburg, Sweden.
    Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving2013In: Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI’13), New York: Association for Computing Machinery (ACM) , 2013, p. 210-217Conference paper (Refereed)
    Abstract [en]

    To investigate the impact of visualizing car uncertainty on drivers' trust during an automated driving scenario, a simulator study was conducted. A between-group design experiment with 59 Swedish drivers was carried out where a continuous representation of the uncertainty of the car's ability to autonomously drive during snow conditions was displayed to one of the groups, whereas omitted for the control group. The results show that, on average, the group of drivers who were provided with the uncertainty representation took control of the car faster when needed, while they were, at the same time, the ones who spent more time looking at other things than on the road ahead. Thus, drivers provided with the uncertainty information could, to a higher degree, perform tasks other than driving without compromising with driving safety. The analysis of trust shows that the participants who were provided with the uncertainty information trusted the automated system less than those who did not receive such information, which indicates a more proper trust calibration than in the control group.

  • 7.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Ohlander, Ulrika
    Saab Aeronautics, Sweden.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Transparency of Automated Combat Classification2014In: Engineering Psychology and Cognitive Ergonomics: 11th International Conference, EPCE 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings / [ed] Don Harris, Springer , 2014, p. 22-33Conference paper (Refereed)
    Abstract [en]

    We present an empirical study where the effects of three levels of system transparency of an automated target classification aid on fighter pilots’ performance and initial trust in the system were evaluated. The levels of transparency consisted of (1) only presenting text–based information regarding the specific object (without any automated support), (2) accompanying the text-based information with an automatically generated object class suggestion and (3) adding the incorporated sensor values with associated (uncertain) historic values in graphical form. The results show that the pilots needed more time to make a classification decision when being provided with display condition 2 and 3 than display condition 1. However, the number of correct classifications and the operators’ trust ratings were the highest when using display condition 3. No difference in the pilots’ decision confidence was found, yet slightly higher workload was reported when using display condition 3. The questionnaire results report on the pilots’ general opinion that an automatic classification aid would help them make better and more confident decisions faster, having trained with the system for a longer period.

  • 8.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Explanation Methods for Bayesian Networks: review and application to a maritime scenario2009In: Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009), University of Skövde , 2009, p. 28-32Conference paper (Refereed)
    Abstract [en]

    Surveillance systems analyze and present vast amounts of heterogeneous sensor data. In order to support operators while monitoring such systems, the identification of anomalous behavior or situations that might need further investigation may reduce operators’ cognitive load. Bayesian networks can be used in order to detect anomalies in data. In order to understand the outcome generated from an anomaly detection application based on Bayesian networks, proper explanations must be given to operators.

    This paper presents the findings of a literature analysis regarding what constitutes an explanation, which properties an explanation may have and a review of different explanation methods for Bayesian networks. Moreover, we present the empirical tests conducted with two of these methods in a maritime scenario. Findings from the survey and the experiments show that explanation methods for Bayesian networks can be used in order to provide operators with more detailed information to base their decisions on.

  • 9.
    Helldin, Tove
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Riveiro, Maria
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Pashami, Sepideh
    Halmstad University, Halmstad, Sweden.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Byttner, Stefan
    Halmstad University, Halmstad, Sweden.
    Nowaczyk, Slawomir
    Halmstad University, Halmstad, Sweden.
    Supporting analytical reasoning: A study from the automotive industry2016In: 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, p. 20-31Conference paper (Refereed)
    Abstract [en]

    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.

    Download full text (pdf)
    FULLTEXT01
  • 10.
    Riveiro, Maria
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Influence of Meta-Information on Decision-Making: Lessons Learned from Four Case Studies2014In: Proceedings of the 4th International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2014), IEEE Communications Society , 2014Conference paper (Refereed)
    Abstract [en]

    This paper discusses the results of four empirical evaluations that assess the effects that visualizing system metainformation have on decision-making, particularly on confidence, trust, workload, time and performance. These four case studies correspond to the analysis of (1) the effects that visualizing uncertainty associated with sensor values (position, speed, altitude, etc. and track quality) have on decision-making on a ground to air defense scenario; (2) the effects that the visualization of the car’s certainty on its own capability of driving autonomously have on drivers’ trust and performance; (3) the influence that the visualization of various qualifiers associated with the proposals given by the support system has on air traffic operators carrying out identification tasks and (4) the effects that the presentation of different abstraction levels of information have on classification tasks carried out by fighter pilots. We summarize the results of these four case studies and discuss lessons learned for the design of future computerized support systems regarding the visualization of meta-information.

  • 11.
    Riveiro, Maria
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Lebram, Mikael
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Effects of visualizing uncertainty on decision-making in a target identification scenario2014In: Computers & graphics, ISSN 0097-8493, E-ISSN 1873-7684, Vol. 41, no 1, p. 84-98Article in journal (Refereed)
    Abstract [en]

    This paper presents an empirical study that addresses the effects the visualization of uncertainty has on decision-making. We focus our investigations on an area where uncertainty plays an important role and the decision time is limited. For that, we selected an air defense scenario, where expert operators have a few minutes to make a well-informed decision based on uncertain sensor data regarding the identity of an object and where the consequences of a late or wrong decision are severe. An approach for uncertainty visualization is proposed and tested using a prototype that supports the interactive analysis of multivariate spatio-temporal sensor data. The uncertainty visualization embeds the accuracy of the sensor data values using the thickness of the lines in the graphical representation of the sensor values. Semi-transparent filled circles represent the uncertain position, while a track quality value between 0 and 1 accounts for the quality of the estimated track for each target. Twenty-two experienced air traffic operators were divided into two groups (with and without uncertainty visualization) and carried out identification and prioritization tasks using the prototype. The results show that the group aided by visualizations of uncertainty needed significantly fewer attempts to make a final identification, and a significant difference between the groups when considering the identities and priorities assigned was observed (participants with uncertainty visualization selected higher priority values and more hostile and suspect identities). These results may show that experts put themselves in the ``worst-case scenario" in the presence of uncertainty when safety is an issue. Additionally, the presentation of uncertainty neither increased the participants' expressed workload, nor the time needed to make a classification. However, the inclusion of the uncertainty information did not have a significant effect on the performance (true positives, false negatives and false positives) or the participants' expressed confidence in their decisions.

  • 12.
    Riveiro, Maria
    et al.
    Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Helldin, Tove
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lebram, Mikael
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Falkman, Göran
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Towards future threat evaluation systems: user study, proposal and precepts for design2013In: Proceedings of the 16th International Conference on Information Fusion, FUSION 2013, IEEE Press , 2013, p. 1863-1870Conference paper (Refereed)
    Abstract [en]

    In the defense domain, to estimate if a targetis threatening and to which degree is a complex task, thatis typically carried out by human operators due to the highrisks and uncertainties associated. To their aid, different supportsystems have been implemented to analyze the data and providerecommendations for actions. Since the ultimate responsibilitylies in human operators, it is of utmost importance that theytrust and know how to use these systems, as well as have anunderstanding of their inner workings, strengths and limitations.This paper presents, first, a formative user study to char-acterize how air traffic operators carry out threat evaluationrelated tasks. Grounded in these findings and in guidelinesfound in the literature, we present a transparent and highlyinteractive prototype that aims at reducing operator’s cognitiveload and support threat assessment activities. The literaturereview provided on design guidelines, the outcomes of the userstudy, the design of the prototype as well as the results of aninitial evaluation can provide guidance for both researchers andprospective developers of future threat evaluation systems.

1 - 12 of 12
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