Authors: Jeffrey Parsons, Roman Lukyanenko
Tags: 2011, citizen science, conceptual modeling, crowdsourcing, data quality, database design
With the proliferation of unstructured data sources and the growing role of crowdsourcing, new data quality challenges are emerging. Traditional approaches that investigated quality in the context of structured relational databases viewed users as data consumers and quality as a product of an information system. Yet, as users increasingly become information producers, a reconceptualization of data quality is needed. This paper contributes by exploring data quality challenges arising in the era of user-supplied information and defines data quality as a function of conceptual modeling choices. The proposed approach can better inform the practice of crowdsourcing and can enable participants to contribute higher quality information with fewer constraints.
Cite as:
Parsons J. and Lukyanenko R. (2011). “Rethinking Data Quality as an Outcome of Conceptual Modeling Choices,” in AIS SIGSAND, Bloomington, IN , United States, June 3-4, 2011.
