An Ontology to support Knowledge Management in Behaviour-based Healthcare

John Kingston, Nathaniel Charlton

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

Abstract

A Do Something Different (DSD) behaviour change programme consists of a series of digitally delivered behavioural prompts, or "Dos", for targeted behaviour change designed to aid people to achieve personal goals or to break bad habits. "Dos" may address for example behaviour connected with exercise, smoking, diet, sleep or diabetes self-management, or personal development objectives such as leadership. DSD's current database contains thousands of such "Dos", developed by behaviour change experts. We have developed an ontology to organise the large database of behavioural prompts in order to help DSD with its knowledge management. We began by developing an ontology of function, bottom-up; then we expanded this into a multi-perspective ontology covering WHO, WHAT, HOW, WHEN, WHERE and WHY perspectives. The expected benefits from our ontology are: 1. response data from users can be aggregated by ontology category to get insights into users' behaviour, 2. the ontology enables the implementation of smarter algorithms for selecting which "Dos" to suggest to which users, and 3. the ontology assists in the process of generating new "Dos", either by domain experts or by crowd-sourcing. Finally we follow an ontology-theoretic approach to argue that our ontology should be re-usable across other behaviour change applications, but maybe not across other application types.
Original languageEnglish
Title of host publicationProceedings of AI-2017, the 37th annual BCS SGAI conference
Place of PublicationCambridge
PublisherSpringer
Pages0-0
Number of pages1
Volume10630
ISBN (Print)9783319710785
DOIs
Publication statusPublished - 21 Nov 2017
EventProceedings of AI-2017, the 37th annual BCS SGAI conference - Peterhouse College, Cambridge, 12-14 December 2017
Duration: 21 Nov 2017 → …

Publication series

NameLecture Notes in Artificial Intelligence

Conference

ConferenceProceedings of AI-2017, the 37th annual BCS SGAI conference
Period21/11/17 → …

Bibliographical note

This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Artificial Intelligence. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-71078-5_19

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