The worldwide Sensor Web comprises observation data from diverse sources. Each data provider may process and assess datasets differently before making them available online. This information is often invisible to end users. Therefore, publishing observation data with quality descriptions is vital as it helps users to assess the suitability of data for their applications. It is also important to...

Structured and encoded information are important to maximize the meaningful (re)use of the Electronic Health Record (EHR). SNOMED CT is generally regarded as the preferred terminology system for encoding, but it has been shown that manual encoding (i.e., fully structured data entry) has issues with data quality and usability. Therefore, automated SNOMED CT encoding of free-text clinical narrati...

This paper reports on a project to develop SOG (Synthetic Occupancy Generator), a system to create realistic, but synthetic residential occupancy (name and address) histories as input for Entity Resolution (ER) processes. ER processes are intended to link records referencing the same, or related, real-world entities. Most organizations use some type of ER process to recognize their customers or...

Huge financial databases may contain terabytes of data and have truly industrial dimensions. Since the quality of conclusions drawn using the data depends primarily on the information quality, the data has to be to monitored using appropriate methods. This paper discusses statistical model-based methods, including process monitoring approaches, applied with respect to the aggregated data, as we...

We present new coarse resolution (0.5× 0.5) vegetation height and vegetation-cover fraction data sets between 60 S and 60 N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global...

This paper compares ve deenitions of data integrity, and shows how they can be ordered in an increasingly restrictive sequence. The most general of these, due to Courtney and Ware 6], is based on the concept of expectation of data quality: data has integrity to the extent that its quality meets, or exceeds, the quality requirements that users expect of it. This deenition incorporates liveness r...

Automatic data acquisition systems provide large amounts of streaming data generated by physical sensors. This data forms an input to computational models (soft sensors) routinely used for monitoring and control of industrial processes, traffic patterns, environment and natural hazards, and many more. The majority of these models assume that the data comes in a cleaned and pre-processed form, r...

The data asset is increasingly becoming one of the top factors in securing organization success. Recognizing the importance of the quality of data, practitioners and researchers have considered for many years ways to improve data quality. Scientists have worked on mathematical and statistical model to introduce constrain based mechanism to prevent data quality problems. Management of the proces...

Organizational and technical changes challenge standards of data warehouse design and initiate a redesign of contemporary Business Intelligence and Analytics environments. As a result, the use of multidimensional models for performance oriented reasons is not necessarily taken for granted. Simple data models or operational structures emerge as a basis for complex analyses. The paper therefore c...

Application service providers (ASPs) and web services are becoming an increasingly popular alternative to selling software the traditional, “shrink-wrapped” way. This paper presents the results of an empirical study of the German ASP market. We surveyed a representative sample of companies traded on the German equivalent of Nasdaq. We asked questions about the companies’ expectations and practi...