One cannot manage information quality (IQ) without first being able to measure it meaningfully and establishing a causal connection between the source of IQ change, the IQ problem types, the types of activities affected, and their implications. In this article we propose a general IQ assessment framework. In contrast to context-specific IQ assessment models, which usually focus on a few variables determined by local needs, our framework consists of comprehensive typologies of IQ problems, related activities, and a taxonomy of IQ dimensions organized in a systematic way based on sound theories and practices. The framework can be used as a knowledge resource and as a guide for developing IQ measurement models for many different settings. The framework was validated and refined by developing specific IQ measurement models for two large-scale collections of two large classes of information objects: Simple Dublin Core records and online encyclopedia articles.
The classic problem within the information quality (IQ) research and practice community has been the problem of defining IQ. It has been found repeatedly that IQ is context sensitive and cannot be described, measured, and assured with a single model. There is a need for empirical case studies of IQ work in different systems to develop a systematic knowledge that can then inform and guide the construction of context-specific IQ models. This article analyzes the organization of IQ assurance work in a large-scale, open, collaborative encyclopediaWikipedia. What is special about Wikipedia as a resource is that the quality discussions and processes are strongly connected to the data itself and are accessible to the general public. This openness makes it particularly easy for researchers to study a particular kind of collaborative work that is highly distributed and that has a particularly substantial focus, not just on error detection but also on error correction. We believe that the study of those evolving debates and processes and of the IQ assurance model as a whole has useful implications for the improvement of quality in other more conventional databases. IntroductionLarge-scale, continuously evolving, open collaborative content creation systems such as Wikipedia have become increasingly popular. At the same time, in an attempt to lower the bottom line, many traditional publishers and informationintensive organizations have opened their content creation processes to the general public by adding wikis and blogs to their regular channels of information creation and distribution. We are witnessing the establishment of a dynamic grid of large-scale, open information systems fueled by active participation from the general public in content creation and quality assurance activities. Although providing valuable information services to the users, the new information grid also poses new and significant challenges in many areas of information organization, including information quality (IQ).These new systems have complex, dynamic workflows that need to react successfully to changes in both their communities and the environment, including identifying the most effective and efficient IQ assurance interventions for different circumstances. Furthermore, the concept of IQ itself is context sensitive (Wang & Strong, 1996). The same information can be judged as being of different quality depending on the context of a particular use and the individual or community value structures for quality. Hence, no one fixed model of IQ assurance can be applied for all these systems. There is a need for empirical studies of existing IQ assurance models, with a goal to develop a knowledge base of conceptual models of IQ, taxonomies of quality problems and activities, metrics, trade-offs, strategies, policies, and references sources. The knowledge base can then be reused for constructing context-specific IQ assurance models faster, cheaper, and with less effort. The English Wikipedia, with its large-scale, complex, and collaborative information...
This article reviews theoretical and empirical studies on information credibility, with particular questions as to how scholars have conceptualized credibility, which is known as a multifaceted concept with underlying dimensions; how credibility has been operationalized and measured in empirical studies, especially in the web context; what are the important user characteristics that contribute to the variability of web credibility assessment; and how the process of web credibility assessment has been theorized. An agenda for future research on information credibility is also discussed.
This article describes a model for online consumer health information consisting of five quality criteria constructs. These constructs are grounded in empirical data from the perspectives of the three main sources in the communication process: health information providers, consumers, and intermediaries, such as Web directory creators and librarians, who assist consumers in finding healthcare information. The article also defines five constructs of Web page structural markers that could be used in information quality evaluation and maps these markers to the quality criteria. Findings from correlation analysis and multinomial logistic tests indicate that use of the structural markers depended significantly on the type of Web page and type of information provider. The findings suggest the need to define genre-specific templates for quality evaluation and the need to develop models for an automatic genre-based classification of health information Web pages. In addition, the study showed that consumers may lack the motivation or literacy skills to evaluate the information quality of health Web pages, which suggests the need to develop accessible automatic information quality evaluation tools and ontologies.
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