Relevance Is in the Eye of the Beholder: Design Principles for the Extraction of Context-aware Information
Abstract
Since the1970s many approaches of representing domains have been suggested. Each approach maintains the assumption that the information about the objects represented in the Information System (IS) is specified and verified by domain experts and potential users. Yet, as more IS are developed to support a larger diversity of users such as customers, suppliers, and members of the general public (such as many multi-user online systems), analysts can no longer rely on a stable single group of people for complete specification of domains—to the extent that prior research has questioned the efficacy of conceptual modeling in these heterogeneous settings. We formulated principles for identifying basic classes in a domain. These classes can guide conceptual modeling, database design, and user interface development in a wide variety of traditional and emergent domains. Moreover, we used a case study of a large foster organization to study how unstructured data entry practices result in differences in how information is collected across organizational units. We used institutional theory to show how institutional elements enacted by individuals can generate new practices that can be adopted over time as best practices. We analyzed free-text notes to prioritize potential cases of psychotropic drug use—our tactical need. We showed that too much flexibility in how data can be entered into the system, results in different styles, which tend to be homogenous across organizational units but not across organizational units. Theories in Psychology help explain the implications of the level of specificity and the inferential utility of the text encoded in the unstructured note.
Subject Area
Business administration|Management|Organizational behavior
Recommended Citation
Castellanos, Arturo, "Relevance Is in the Eye of the Beholder: Design Principles for the Extraction of Context-aware Information" (2016). ProQuest ETD Collection for FIU. AAI10259411.
https://digitalcommons.fiu.edu/dissertations/AAI10259411