Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring

Hearst, Marti A.; Laskowski, Paul; Silva, Luis

doi:10.1145/2858036.2858280

Cited by 28 publications

(11 citation statements)

References 28 publications

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“…• used crowdsourcing only for the pilot study (e.g., [TGH12]); • used crowdsourcing not for evaluation but for other purposes such as data collection (e.g., user generated layouts [KDMW16, KWD14, vHR08]); • evaluated graphics but no information visualization (e.g., [ • discussed previous crowdsourcing studies without using crowdsourcing (e.g., [AJB16, ZGB * 17, KH16]); • mentioned the use of crowdsourcing for future evaluation (e.g., [HLS16]).…”

Section: Methodsmentioning

confidence: 99%

Information Visualization Evaluation Using Crowdsourcing

Borgo

Micallef

Bach

et al. 2018

Computer Graphics Forum

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Visualization researchers have been increasingly leveraging crowdsourcing approaches to overcome a number of limitations of controlled laboratory experiments, including small participant sample sizes and narrow demographic backgrounds of study participants. However, as a community, we have little understanding on when, where, and how researchers use crowdsourcing approaches for visualization research. In this paper, we review the use of crowdsourcing for evaluation in visualization research. We analyzed 190 crowdsourcing experiments, reported in 82 papers that were published in major visualization conferences and journals between 2006 and 2017. We tagged each experiment along 36 dimensions that we identified for crowdsourcing experiments. We grouped our dimensions into six important aspects: study design & procedure, task type, participants, measures & metrics, quality assurance, and reproducibility. We report on the main findings of our review and discuss challenges and opportunities for improvements in conducting crowdsourcing studies for visualization research.

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Section: Methodsmentioning

confidence: 99%

Information Visualization Evaluation Using Crowdsourcing

Borgo

Micallef

Bach

et al. 2018

Computer Graphics Forum

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“…A query and visualisation evaluation was conducted to assess the efficiency of the visualisation system in delivering visualised content to users ( Amri, Ltifi & Ayed, 2015 ; Hearst, Laskowski & Silva, 2016 ). This helps measure the performance of query sending from the GUI to the server and translates the results into a visual format.…”

Section: Methodsmentioning

confidence: 99%

Plant data visualisation using network graphs

Mohamad-Matrol

Chang

Abu

2018

PeerJ

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BackgroundThe amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the public to discern meaningful relationships from this vast amount of data using appropriate methods. The data are often presented in lengthy texts and tables, which make gaining new insights difficult. The study proposes a visual-based representation to display data to users in a meaningful way. This method emphasises the relationships between different data sets.MethodThis study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation.ResultsA visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation.DiscussionThe relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.

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“…There are different approaches to bringing usability or playability into development, from player-centered design models such as in Charles and colleagues [9] to heuristic evaluation such as in Desurwire and Wiberg [13]. One of the simplest ways to enhance usability is to introduce heuristics that can be used by every team member, without the need of usability professionals [28], [38], [50], [66]: they provide a cheap and flexible tool for finding issues early and to better understand usability and/or playability [53] that can be used by novice evaluators with good results [22]. Usability heuristics for games were first introduced by Malone [39] in 1980.…”

Section: Usability and Gamesmentioning

confidence: 99%

The Quest for Usable Usability Heuristics for Game Developers

Mylly

Rajanen

Iivari

2020

Lecture Notes in Information Systems and Organisation

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Human Computer Interaction (HCI) research has provided many processes and methods for ensuring good usability during software development. The importance of usability in games has been acknowledged. However, there is a lack of research examining usability activities during actual game development and the suitability of different usability methods for different phases of game development. Game development industry, although growing fast and already including certain large and successful companies, consists of a huge number of small-to-medium-sized enterprises and start-ups. For these companies, practical, developer-oriented tools for ensuring game usability are needed, as these companies do not have resources for hiring usability specialists for taking care of usability. This paper reviews the concept of game usability and existing research on usability methods for game development. In addition, the paper proposes a set of usable usability heuristics as a practical, developer-oriented tool to be used during the game development process as well as reports on a small-scale survey study on game usability, heuristic evaluation and usability of usability heuristics in game development.

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Evaluating Information Visualization via the Interplay of Heuristic Evaluation and Question-Based Scoring

Cited by 28 publications

References 28 publications

Information Visualization Evaluation Using Crowdsourcing

Information Visualization Evaluation Using Crowdsourcing

Plant data visualisation using network graphs

The Quest for Usable Usability Heuristics for Game Developers

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