title: A scope classification of data quality requirements for food composition data.
abstract: Data quality is an important issue when managing food composition data since the usage of the data can have a significant influence on policy making and further research. Although several frameworks for data quality have been proposed, general tools and measures are still lacking. As a first step in this direction, we investigated data quality requirements for an information system to manage food composition data, called FoodCASE. The objective of our investigation was to find out if different requirements have different impacts on the intrinsic data quality that must be regarded during data quality assessment and how these impacts can be described. We refer to the resulting classification with its categories as the scope classification of data quality requirements. As proof of feasibility, the scope classification has been implemented in the FoodCASE system.
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, Switzerland. Electronic address: karl.presser@inf.ethz.ch.
authors.forename: Karl
authors.initials: K
authors.lastname: Presser
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, Switzerland.
authors.forename: Hans
authors.initials: H
authors.lastname: Hinterberger
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, Switzerland.
authors.forename: David
authors.initials: D
authors.lastname: Weber
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, Switzerland.
authors.forename: Moira
authors.initials: M
authors.lastname: Norrie
mesh_terms: D000068598:Data Accuracy; D005502:Food; D005504:Food Analysis / Q000145:classification / Q000592:standards*; D063427:Food Quality; D006801:Humans; D009753:Nutritive Value
keywords: Classification of requirements; Data quality; Food composition data