ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / There is great potential in using Best Source Selectors (BSS) to improve link availability in aeronautical telemetry applications. While the general notion that diverse data sources can be used to construct a consolidated stream of "better" data is well founded, there is no standardized means of determining the quality of the data streams being merged together. Absent this uniform quality data, the BSS has no analytically sound way of knowing which streams are better, or best. This problem is further exacerbated when one imagines that multiple vendors are developing data quality estimation schemes, with no standard definition of how to measure data quality. In this paper, we present measured performance for a specific Data Quality Metric (DQM) implementation, demonstrating that the signals present in the demodulator can be used to quickly and accurately measure the data quality, and we propose test methods for calibrating DQM over a wide variety of channel impairments. We also propose an efficient means of encapsulating this DQM information with the data, to simplify processing by the BSS. This work leads toward a potential standardization that would allow data quality estimators and best source selectors from multiple vendors to interoperate.

This master thesis is concerned with the choice of suitable data quality dimensions for a particular database of economy information and proposes and implements metrics for its assessment. The aim of this paper is to define the term data quality in the context of economy information database and possible ways to measure it. Based on dimensions suitable to observe, a list of metrics was created and subsequently implemented in SQL query language, alternatively in a procedural extension Transact SQL. These metrics were also tested with the use of real data and the results were provided with a commentary. The main asset of this work is its complex processing of the data quality topic, from theoretical term definition to particular implementation of individual metrics. Finally, this study offers a variety of both theoretical and practical directions fort this issue to be further researched.

The master thesis deals with data quality in the context of open and linked data. One of the goals is to define specifics of data quality in this context. The specifics are perceived mainly with orientation to data quality dimensions (i. e. data characteristics which we study in data quality) and possibilities of their measurement. The thesis also defines the effect on data quality that is connected with data transformation to linked data; the effect if defined with consideration to possible risks and benefits that can influence data quality. The list of metrics verified on real data (open linked data published by government institution) is composed for the data quality dimensions that are considered to be relevant in context of open and linked data. The thesis points to the need of recognition of differences that are specific in this context when assessing and managing data quality. At the same time, it offers possibilities for further study of this question and it presents subsequent directions for both theoretical and practical evolution of the topic.