http://hdl.handle.net/1721.1/1792 http://dspace.mit.edu:80/retrieve/5829 http://hdl.handle.net/1721.1/1792 http://hdl.handle.net/1721.1/40087 Semantic Integration Approach to Efficient Business Data Supply Chain: Integration Approach to Interoperable XBRL Zhu, Hongwei Madnick, Stuart E. As an open standard for electronic communication of business and financial data, XBRL has the potential of improving the efficiency of the business data supply chain. A number of jurisdictions have developed different XBRL taxonomies as their data standards. Semantic heterogeneity exists in these taxonomies, the corresponding instances, and the internal systems that store the original data. Consequently, there are still substantial difficulties in creating and using XBRL instances that involve multiple taxonomies. To fully realize the potential benefits of XBRL, we have to develop technologies to reconcile semantic heterogeneity and enable interoperability of various parts of the supply chain. In this paper, we analyze the XBRL standard and use examples of different taxonomies to illustrate the interoperability challenge. We also propose a technical solution that incorporates schema matching and context mediation techniques to improve the efficiency of the production and consumption of XBRL data. Fri, 11 Jan 2008 18:30:18 GMT http://hdl.handle.net/1721.1/40086 Measuring Data Believability: A Provenance Approach Prat, Nicolas Madnick, Stuart E. Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of quality, measured along three dimensions: trustworthiness, reasonableness, and temporality. We ground our approach on provenance, i.e. the origin and subsequent processing history of data. We present our provenance model and our approach for computing believability based on provenance metadata. The approach is structured into three increasingly complex building blocks: (1) definition of metrics for assessing the believability of data sources, (2) definition of metrics for assessing the believability of data resulting from one process run and (3) assessment of believability based on all the sources and processing history of data. We illustrate our approach with a scenario based on Internet data. To our knowledge, this is the first work to develop a precise approach to measuring data believability and making explicit use of provenance-based measurements. Fri, 11 Jan 2008 18:24:10 GMT http://hdl.handle.net/1721.1/40085 Evaluating and Aggregating Data Believability across Quality Sub-Dimensions and Data Lineage Prat, Nicolas Madnick, Stuart E. Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of data quality. The issue of believability is particularly relevant in the context of Web 2.0, where mashups facilitate the combination of data from different sources. Our approach for assessing data believability is based on provenance and lineage, i.e. the origin and subsequent processing history of data. We present the main concepts of our model for representing and storing data provenance, and an ontology of the sub-dimensions of data believability. We then use aggregation operators to compute believability across the sub-dimensions of data believability and the provenance of data. We illustrate our approach with a scenario based on Internet data. Our contribution lies in three main design artifacts (1) the provenance model (2) the ontology of believability subdimensions and (3) the method for computing and aggregating data believability. To our knowledge, this is the first work to operationalize provenance-based assessment of data believability. Fri, 11 Jan 2008 18:15:00 GMT http://hdl.handle.net/1721.1/40084 Enabling Global Price Comparison through Semantic Integration of Web Data Zhu, Hongwei Siegel, Michael Madnick, Stuart “Sell Globally” and “Shop Globally” have been seen as a potential benefit of web-enabled electronic business. One important step toward realizing this benefit is to know how things are selling in various parts of the world. A global price comparison service would address this need. But there have not been many such services. In this paper, we use a case study of global price dispersion to illustrate the need and the value of a global price comparison service. Then we identify and discuss several technology challenges, including semantic heterogeneity, in providing a global price comparison service. We propose a mediation architecture to address the semantic heterogeneity problem, and demonstrate the feasibility of the proposed architecture by implementing a prototype that enables global price comparison using data from web sources in several countries. Fri, 11 Jan 2008 18:04:18 GMT