Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: On-demand curation (ODC) tools like Paygo, KATARA, and Mimir allow users to defer expensive curation effort until it is necessary. In contrast to classical databases that do not respond to queries over potentially erroneous data, ODC systems instead ansr with guesses or approximations. The quality and scope of these guesses may vary and it is critical that an ODC system be able to communicate this information to an end-user. The central contribution of this paper is a preliminary user study evaluating the cognitive burden and expressiveness of four representations of "attribute-level" uncertainty. The study shows (1) insignificant differences in time taken for users to interpret the four types of uncertainty tested, and (2) that different presentations of uncertainty change the way people interpret and react to data. Ultimately,  show that a set of UI design guidelines and best practices for conveying uncertainty will be necessary for ODC tools to be effective.  represents the first step towards establishing such guidelines.
['Poonam Kumari', 'Said Achmiz', 'Oliver Kennedy']
I am writing a research paper on a idea Communicating Data Quality in On-Demand Curation
[{"from": "human", "value": "I am writing a research paper on a idea Communicating Data Quality in On-Demand Curation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: On-demand curation (ODC) tools like Paygo, KATARA, and Mimir allow users to defer expensive curation effort until it is necessary. In contrast to classical databases that do not respond to queries over potentially erroneous data, ODC systems instead ansr with guesses or approximations. The quality and scope of these guesses may vary and it is critical that an ODC system be able to communicate this information to an end-user. The central contribution of this paper is a preliminary user study evaluating the cognitive burden and expressiveness of four representations of \"attribute-level\" uncertainty. The study shows (1) insignificant differences in time taken for users to interpret the four types of uncertainty tested, and (2) that different presentations of uncertainty change the way people interpret and react to data. Ultimately,  show that a set of UI design guidelines and best practices for conveying uncertainty will be necessary for ODC tools to be effective.  represents the first step towards establishing such guidelines."}]