In the social sciences, data is often collected in so-called 'longitudinal studies' from people aged 50 and over - various measurements of health, economic and social circumstances, mobility and finances, and so on, are used to analyse trends and make forecasts within a certain demographic.
Various physical, lifestyle, mental health (cognition), and other measures are used in subsequent publications, such as:
Goals of this challenge:
- Find and select a sample of open data (i.e. processed, anonymized and republishable) relevant to this challenge. Search through open data portals, or see here for a list of links that we started.
- Analyse and visualise demographics similar to the kinds used in a social sciences study on ageing.
- Design a citizen science application where people could volunteer more study data online.
- Prototype and deploy this "My Data" application, build-in APIs or open data exports.
Bonus questions to explore:
- what compels or distracts from participating in studies - could people be encouraged to collect their own data?
- are there interesting new ways to gather the data, e.g. through online surveys, apps and other digital tools?
- how much effort is involved in understanding and analysing such data, how does it inform - how can it mislead?
- can this type of data be effectively anonymized, and what risks are there in unauthorised disclosure?
- what approaches would there be to make citizen science a part of collecting and (re)using this information?
- which standards, formats, platforms could be most supportive of Open Science and open research data sharing?
For further information see presentations by Rufus Pollock and others at the recent MyData 2016 conference. This challenge was submitted by the Opendata.ch association.
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