In this paper, we propose an original methodology by which to assess the construct of the situated social value of open data and we apply it to the healthcare domain in regard to information by which hospitals can be ranked to compare service providers. Our methodology encompasses a questionnaire-based user study and a method by which to rank information items by their perceived social value in situated scenarios. While the social component of the construct is addressed traditionally, the main asset of our contribution is to ground the assessment of information value on a multidimensional space of potential situations where that information can be perceived as valuable, and to inquiry the respondents of the user study about their empathized perceptions in daily life scenarios, which are defined to cover the dimensional space properly. The findings of the user study are reported and the implications on the construct assessment discussed in the aim to enable IS benchmarking and more focused interventions of data quality improvement.
A User Study to Assess the Situated Social Value of Open Data in Healthcare
Locoro A.;
2015-01-01
Abstract
In this paper, we propose an original methodology by which to assess the construct of the situated social value of open data and we apply it to the healthcare domain in regard to information by which hospitals can be ranked to compare service providers. Our methodology encompasses a questionnaire-based user study and a method by which to rank information items by their perceived social value in situated scenarios. While the social component of the construct is addressed traditionally, the main asset of our contribution is to ground the assessment of information value on a multidimensional space of potential situations where that information can be perceived as valuable, and to inquiry the respondents of the user study about their empathized perceptions in daily life scenarios, which are defined to cover the dimensional space properly. The findings of the user study are reported and the implications on the construct assessment discussed in the aim to enable IS benchmarking and more focused interventions of data quality improvement.File | Dimensione | Formato | |
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