Contextual information quality assessment methodology in data processing using the manufacturing of information approach

Studies have shown that data-quality (DQ) and information-quality (IQ) assessment are essential activities in organizations that want to improve the efficiency of communication and information systems. So far, research on the evaluation of DQ and IQ has focused on approaches, models or classification of attributes. However, context-specific DQ and IQ assessment methodologies are difficult to find in the literature. While assessment methodologies do exist for office document processing in general, there are none for forms. The focus of this thesis is the need for a context-specific tool with which to assess the DQ input and the IQ output in communication and information systems. The channel analysed for this purpose is the form. This thesis proposes a novel methodology based on: 1) an adaptation of the “manufacturing of information” approach, which adopts the communication-system point of view; 2) an existing DQ classification system that classifies attributes as intrinsic, contextual, representational or accessible; and 3) a new conceptual model which provides the guidelines for assessment of forms. This evaluation only takes into consideration established contextual attributes, such as completeness, appropriate amount of data (here called “sufficiency”), relevance (which emphasises content), timeliness (which emphasises process) and actual value. To present the applicability of the contextual-information quality assessment (CIQA) methodology, two representative forms were used as case studies. The main results suggest that a novel data representation allows data to be classified by type (indispensable or verification) and composition (simple or composite). In one of the two case studies, the data quantity was reduced by 50%, resulting in a 15% improvement of IQ and a more efficient document processing system. The streamlining and new structure of the form led not only to a reduction in data quantity but also to increased information quality. This suggests that data quantity is not directly correlated to IQ, as IQ may increase in the absence of a corresponding increase in data quantity. In addition, the design of the forms requires particular attention to content, not simply aesthetics. Furthermore, in data processing, there could be great benefits in combining IQ assessment and computerization processes, in order to avoid problems such as data overload; of course, data security would need to be considered as well