Data Enablement for SDG 3 “Health and Wellbeing”
Individuals are increasingly engaged in indicators data monitoring, through personal informatics, life-logging, quantified self, and from IoT sensor data. This research focuses on SDG 3 “health and wellbeing” and investigates individuals’ current data collection and monitoring practice; explores motivations and incentives for data use; investigates data utility, sharing and social sense-making; and explores data enablement through technology.
RATIONALE & MOTIVATION
The increasing ubiquity of data in society is not only seen in the increased use in organizations but also in increased data use by individuals in areas such as life-logging, associated with the proliferation of activity trackers and mobile devices. There has been increasing efforts and research around the use of data for informing individual wellbeing goals and imperatives. The growing field of personal informatics, quantified-self, and lived informatics represent this interest and focus on data that is collected by individuals for the ultimate utility that accrues towards the individuals. These developments present an opportunity for the engagement of individuals not only in action towards the achievement, but also in the monitoring of progress towards the relevant Sustainable Development Goals.
The following are the key questions formulated for this research:
- What are the current practices of individuals with regards to monitoring indicators for SDG 3?
- What are the individuals’ views and attitudes towards indicators monitoring, data collection, data sharing, and social sense-making?
- What is the role of technology to support indicators monitoring by individuals?
RESEARCH OBJECTIVES & METHODS
This research utilizes an online survey instrument, with recruited virtual participants, to address research questions 1 and 2 above. The survey instrument, comprising of close-ended and open-ended questions, is framed along the following lines of inquiry: current data collection and monitoring practice; motivations and incentives for data use; and data utility, sharing and social sense-making. A mixed method approach (specifically convergent parallel design) combining descriptive statistics for the quantitative data, and template analysis for the qualitative data is utilized for the analysis of the survey data.
Informed by the findings from the survey, the research develops an ICT tool for indicators monitoring, and assesses its utilization towards data enablement of individuals for monitoring SDG 3.
Sustainable Development, Personal informatics, Indicators Monitoring
- Thinyane, M. (2017b). Small data and sustainable development — Individuals at the center of data-driven societies. In 2017 ITU Kaleidoscope: Challenges for a Data-Driven Society (ITU K) (pp. 1–8). IEEE.