human activities in the recent years have considerably increased the rate of water pollution in many regions of the world. in this case study, the main sources of wastewater discharging into the gargar river were identified. using river and point source flow rates and water quality parameters measured along the river, the river water quality was simulated using a commonly used, one-dimensional ...

In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R(merge) values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R(merge) values are poorly suited for determining the high-resolution limit and that c...

With the increasing amount of Linked Data published on the Web, the community has recognised the importance of the quality of such data and a number of initiatives have been undertaken to specify and evaluate Linked Data quality. However, these initiatives are characterised by a high diversity in terms of the quality aspects that they address and measure. This leads to difficulties in comparing...

This paper examines the effect of the order of a system redesign process on the quality of the information. A process that focuses on understanding the business model and the data prior to making technical decisions can produce information of higher quality, while continual use of patches and technology solutions can reduce the system’s data quality. The study of a global financial institution ...

One of the major causes for the failure of information systems to deliver can be attributed to data quality. Gartner’s figures and other similar studies show the failure rate hovering at a plateau of 50% for data warehouses since 2004. While the true cause of poor data quality can be attributed to a lack of supporting business processes, insufficient analysis techniques, along with protecting o...

Measurement is a key activity in DQ Management. Through DQ literature, one can discover a lot of proposals contributing somehow to the measurement of DQ issues. Looking at those proposals, it can be found out that there is a lack of unification of the nomenclature: different authors call to the same concepts in different way, or even, they do not explicitly recognize some of them. This may caus...

Data Quality (DQ) is a critical issue for effective asset management. DQ problems can result in severe negative consequences for an organisation. Several research studies have indicated that most organizations have DQ problems. This paper aims to explore DQ issues associated with the implementation of Enterprise Asset Management (EAM) systems. The study applies a DQ research framework for Asset...

Linked (Open) Data (LD) offer the great opportunity to interconnect and share large amounts of data on a global scale, creating added value compared to data published via pure HTML. However, this enormous potential is not completely accessible. In fact, LD datasets are often affected by errors, inconsistencies, missing values and other quality issues that may lower their usage. Users are often ...

In an earlier paper we introduced Anchoring, a new approach for handling indeterminate location in a spatial information system. Here we develop it further, showing how Anchoring can be made to work in real systems. In particular, we specify a new kind of locational component for a spatial data model. We then show how that component can be implemented into an object-relational database with ext...