Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making

Brian Cleland; Jonathan Wallace; Raymond Bond; Salla Muuraiskangas; Juha Pajula; Gorka Epelde; Mónica Arrúe; Roberto Álvarez; Michaela Black; Maurice D. Mulvenna; Deborah Rankin; Paul Carlin

doi:10.1007/978-3-030-22660-2_13

Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making

Brian Cleland, Jonathan Wallace, Raymond Bond, Salla Muuraiskangas, Juha Pajula, Gorka Epelde, Mónica Arrúe, Roberto Álvarez, Michaela Black, Maurice D. Mulvenna, Deborah Rankin, Paul Carlin

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

1 Citation (Scopus)

Abstract

The increasingly important role of big data in organisational decision-making brings with it significant challenges in terms of designing usable software interfaces. Specifically, such interfaces must allow users to explore, analyse, and visualise complex data from heterogeneous sources and derive insights to support management decisions. This paper describes a usability evaluation of the MIDAS Project, a big data platform for health policy-making, developed by an EU-funded Horizon 2020 project involving a number of international partners and pilot sites. We describe how a combination of heuristic and formative user-centred evaluation methods were employed, and give a summary of the key findings. We discuss key insights from the evaluation, including the importance of having diverse users, the role played by users’ prior expectations, and the logistical challenge of coordinating user testing across multiple sites. Finally, we explore the relative value of each of the evaluation methods, and outline how our approach to usability testing will evolve for future iterations of the MIDAS platform.

Original language	English
Title of host publication	Human Interface and the Management of Information
Subtitle of host publication	Visual Information and Knowledge Management, HCII 2019
Editors	Sakae Yamamoto, Hirohiko Mori
Publisher	Springer
Pages	194-207
Number of pages	14
ISBN (Electronic)	978-3-030-22660-2
ISBN (Print)	978-3-030-22659-6
DOIs	https://doi.org/10.1007/978-3-030-22660-2_13
Publication status	Published - 2019
MoE publication type	A4 Article in a conference publication
Event	Thematic Area on Human Interface and the Management of Information, HIMI 2019 : held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States Duration: 26 Jul 2019 → 31 Jul 2019

Publication series

Series	Lecture Notes in Computer Science
Volume	11569
ISSN	0302-9743

Conference

Conference	Thematic Area on Human Interface and the Management of Information, HIMI 2019
Country	United States
City	Orlando
Period	26/07/19 → 31/07/19

Keywords

Big data
Evaluation
Health
Policy-making
Usability
User-centred

Access to Document

10.1007/978-3-030-22660-2_13

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Cleland, B., Wallace, J., Bond, R., Muuraiskangas, S., Pajula, J., Epelde, G., Arrúe, M., Álvarez, R., Black, M., Mulvenna, M. D., Rankin, D., & Carlin, P. (2019). Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making. In S. Yamamoto, & H. Mori (Eds.), Human Interface and the Management of Information: Visual Information and Knowledge Management, HCII 2019 (pp. 194-207). Springer. Lecture Notes in Computer Science Vol. 11569 https://doi.org/10.1007/978-3-030-22660-2_13

Cleland, Brian ; Wallace, Jonathan ; Bond, Raymond ; Muuraiskangas, Salla ; Pajula, Juha ; Epelde, Gorka ; Arrúe, Mónica ; Álvarez, Roberto ; Black, Michaela ; Mulvenna, Maurice D. ; Rankin, Deborah ; Carlin, Paul. / Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making. Human Interface and the Management of Information: Visual Information and Knowledge Management, HCII 2019. editor / Sakae Yamamoto ; Hirohiko Mori. Springer, 2019. pp. 194-207 (Lecture Notes in Computer Science, Vol. 11569).

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title = "Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making",

abstract = "The increasingly important role of big data in organisational decision-making brings with it significant challenges in terms of designing usable software interfaces. Specifically, such interfaces must allow users to explore, analyse, and visualise complex data from heterogeneous sources and derive insights to support management decisions. This paper describes a usability evaluation of the MIDAS Project, a big data platform for health policy-making, developed by an EU-funded Horizon 2020 project involving a number of international partners and pilot sites. We describe how a combination of heuristic and formative user-centred evaluation methods were employed, and give a summary of the key findings. We discuss key insights from the evaluation, including the importance of having diverse users, the role played by users{\textquoteright} prior expectations, and the logistical challenge of coordinating user testing across multiple sites. Finally, we explore the relative value of each of the evaluation methods, and outline how our approach to usability testing will evolve for future iterations of the MIDAS platform.",

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Cleland, B, Wallace, J, Bond, R, Muuraiskangas, S , Pajula, J, Epelde, G, Arrúe, M, Álvarez, R, Black, M, Mulvenna, MD, Rankin, D & Carlin, P 2019, Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making. in S Yamamoto & H Mori (eds), Human Interface and the Management of Information: Visual Information and Knowledge Management, HCII 2019. Springer, Lecture Notes in Computer Science, vol. 11569, pp. 194-207, Thematic Area on Human Interface and the Management of Information, HIMI 2019 , Orlando, United States, 26/07/19. https://doi.org/10.1007/978-3-030-22660-2_13

Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making. / Cleland, Brian; Wallace, Jonathan; Bond, Raymond; Muuraiskangas, Salla ; Pajula, Juha; Epelde, Gorka; Arrúe, Mónica; Álvarez, Roberto; Black, Michaela; Mulvenna, Maurice D.; Rankin, Deborah; Carlin, Paul.

Human Interface and the Management of Information: Visual Information and Knowledge Management, HCII 2019. ed. / Sakae Yamamoto; Hirohiko Mori. Springer, 2019. p. 194-207 (Lecture Notes in Computer Science, Vol. 11569).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Muuraiskangas, Salla

AU - Pajula, Juha

AU - Epelde, Gorka

AU - Arrúe, Mónica

AU - Álvarez, Roberto

AU - Black, Michaela

AU - Mulvenna, Maurice D.

AU - Rankin, Deborah

AU - Carlin, Paul

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AB - The increasingly important role of big data in organisational decision-making brings with it significant challenges in terms of designing usable software interfaces. Specifically, such interfaces must allow users to explore, analyse, and visualise complex data from heterogeneous sources and derive insights to support management decisions. This paper describes a usability evaluation of the MIDAS Project, a big data platform for health policy-making, developed by an EU-funded Horizon 2020 project involving a number of international partners and pilot sites. We describe how a combination of heuristic and formative user-centred evaluation methods were employed, and give a summary of the key findings. We discuss key insights from the evaluation, including the importance of having diverse users, the role played by users’ prior expectations, and the logistical challenge of coordinating user testing across multiple sites. Finally, we explore the relative value of each of the evaluation methods, and outline how our approach to usability testing will evolve for future iterations of the MIDAS platform.

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Cleland B, Wallace J, Bond R, Muuraiskangas S , Pajula J, Epelde G et al. Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making. In Yamamoto S, Mori H, editors, Human Interface and the Management of Information: Visual Information and Knowledge Management, HCII 2019. Springer. 2019. p. 194-207. (Lecture Notes in Computer Science, Vol. 11569). https://doi.org/10.1007/978-3-030-22660-2_13