Boyes, Peter
(2023)
Negotiating the truth: exploring the influence of metadata in place-related group decision making.
PhD thesis, University of Nottingham.
Abstract
The spread of technologies like the Internet of Things has increased data collection and availability to decision makers. This inherently messy and complex data, growing in volume, is being used to inform strategic decision making in settings such as smart cities to monitor, manage, and develop the urban spaces. Commonly this strategic decision making is carried out by multidisciplinary groups under influential conditions such as time pressure and uncertainty. These decision makers are not necessarily experts or trained data analysts, and it’s a difficult task to assess the quality of data they are using. Provision of data quality metadata can alleviate issues of uncertainty but present a similar challenge of interpretation by non-experts. Abstractions and visualisations can make this data quality accessible and can improve decision outcomes by tackling uncertainty. An exploratory study establishes a grounding for issues facing decision making groups on a university campus. This first study presented is a series of semi structured interviews run with six members of Higher Education sector capital project management groups. Individual interviews with these representatives of multidisciplinary stakeholder groups produced a corpus for thematic analysis, validating current theory and identifying opportunities for technical intervention. Interview questions were based around; roles and representation, project drivers, working processes, data use, decision support tools, and project challenges and reflections. An experimental study then investigates the design and assessment of a decision support tool that provides decision making teams with a traffic light abstraction of data quality metadata. A serious game approach uses a local pandemic response scenario to explore group decision making and a support tool intervention. A convenience sampling method recruited 9 groups of 4 non-domain experts to use a bespoke browser-based decision support tool and MS Teams to complete a resource allocation task. An ethnographic approach is used to observe the groups in the sensemaking and decision making process. Qualitative focus groups are used after completion of the task to augment interactions with the tool logged during the session and the decision outcomes. The evaluation of the intervention considers the effects on decision outcomes, decision confidence, data trust, and the decision process in a medium-time-pressured vaccination site selection task. The main contribution is the development and study of a bespoke decision support tool that assesses the impact of a visual abstraction of data quality metadata on group trust in data under a medium time pressure. In an engaging scenario the map-based tool shows how the technical intervention improved trust of non-domain experts in the data used in their decision making, without negative effects that introduction of detailed data quality metadata caused. Detailed metadata on the other hand was introduced to the detriment of decision outcomes, lower trust in data, and lower confidence in the decision made. The abstraction and implementation demonstrated a working method of engendering trust in data under time pressure to novice users of decision support tools and non-domain experts with respect to the data. The research contributes in a qualitative way the agreement across participants on the high trust in spatial and perceived easy-to-collect data, while highlighting the disagreement dependent on metadata abstraction over other data types such as projected datasets. No difference is found in task performance and confidence in decision outcomes when providing abstracted metadata and no metadata, though both are improvements on detailed metadata. The results show how abstracted metadata encouraged greater data quality assessment and trust building behaviour than non-metadata or detailed metadata groups. A framework for characterisation of decision making settings by the temporality of the data being used and the time pressure of the decision being made is offered for validation. This model could help researchers in identifying and comparing decision making scenarios and related findings, estimating transferability of results and hypotheses. The study also elicited several factors that impacted the trust in data, the influences on how individuals perceive the data source or collection, such as perceived ease of accurate data collection. Recommendations are given for directions of future work that combine the findings of the studies in this PhD with the state of the relevant literature. A selection of models from the related work are reconsidered, and amendments or extensions are recommended to incorporate the findings on data trust and uncertainty from this research.
| Item Type: |
Thesis (University of Nottingham only)
(PhD)
|
| Supervisors: |
Tennent, Paul
Priestnall, Gary
Sharples, Sarah
Morley, Jeremy |
| Keywords: |
Data trust; Data uncertainty; Decision making; Abstracted metadata |
| Subjects: |
T Technology > T Technology (General) |
| Faculties/Schools: |
UK Campuses > Faculty of Science > School of Computer Science |
| Item ID: |
76607 |
| Depositing User: |
Boyes, Peter
|
| Date Deposited: |
09 Apr 2024 13:58 |
| Last Modified: |
09 Apr 2024 13:58 |
| URI: |
https://eprints.nottingham.ac.uk/id/eprint/76607 |
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