15368609
Data quality in context
ATA-QUALITY (DQ) PROBLEMS ARE INCREASINGLY EVIdent, particularly in organizational databases. Indeed, 50% to 80% of computerized criminal records in the U.S. were found to be inaccurate, incomplete, or ambiguous. The social and economic impact of poor-quality data costs billions of dollars. [5-7, 10]. Organizational databases, however, reside in the larger context of information systems (IS). Within this larger context, data is collected from multiple data sources and stored in databases. From this stored data, useful information is generated for organizational decision-making. A new study reveals businesses are defining data quality with the consumer in mind.
12254873
Process Knowledge and Data Quality Outcomes
What modes and domains of knowledge about data production processes are most critical for producing high-quality data? This study provides an answer to this question. Data are collected via questionnaire and analyzed using linear regression. The results show some similarities and differences in which knowledge variables are significant for various data quality dimensions. Three results are of particular interest to data quality managers and researchers. The first is the complexity and mix of knowledge associated with producing accurate data. The second is the significant results overall for knowledge about the data collection process as compared to data storage and utilization processes. The third is the negative associations of the knowing-why mode of knowledge as compared to the positive associations for knowing-what and knowing-how. Each of these results has managerial implications and generates avenues for further research.
5961676
Total Data Quality Management: The Case of IRI
Abstract Implementing a Total Data Quality Management (TDQM) program is not a trivial undertaking. Two key steps are (1) to clearly define what an organization means by data quality and (2) to develop metrics that measure data quality dimensions and that are linked to the organization’s goals and objectives. This paper presents the case of Information Resources, Inc., which exemplifies how a company can develop a viable TDQM program.
207563187
Data quality assessment
How good is a company's data quality? Answering this question requires usable data quality metrics. Currently, most data quality measures are developed on an ad hoc basis to solve specific problems [6, 8], and fundamental principles necessary for developing usable metrics in practice are lacking. In this article, we describe principles that can help organizations develop usable data quality metrics.
13163414
Process-Embedded Data Integrity
Despite the established theory and the history of the practical use of integrity rules, data quality problems, which should be solvable using data integrity rules, persist in organizations. One effective mechanism to solve this problem is to embed data integrity in a continuous data quality improvement process. The result is an iterative data quality improvement process as data integrity rules are defined, violations of these rules are measured and analyzed, and then the rules are redefined to reflect the dynamic and global context of business process changes. Using action research, we study a global manufacturing company that applied these ideas for improving data quality as it built a global data warehouse. This research merges data integrity theory with management theories about quality improvement using a data quality lens, and it demonstrates the usefulness of the combined theory for data quality improvement.
31460995
Voltage-Clock Scaling for Low Energy Consumption in Fixed-Priority Real-Time Systems
Power and energy constraints are becoming increasingly prevalent in real-time embedded systems. Voltage-scaling is a promising technique to reduce energy and power consumption: clock speed tends to decrease linearly with supply voltage while power consumption goes down quadratically. We therefore have a tradeoff between the energy consumption of a task and the speed with which it can be completed. The timing constraints associated with real-time tasks can be used to resolve this tradeoff. In this paper, we present two algorithms for voltage-scaling. Assuming that a processor can operate in one of two modes: high voltage and low voltage, we show how to schedule the voltage settings so that deadlines are met while reducing the total energy consumed. We show that significant reductions can be made in energy consumption.
9259468
Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data
MOTIVATION
High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.


RESULTS
Its applicability is demonstrated on the leukemia data (Golub et al., 1999) and the small round blue cell tumors of childhood data (Khan et al., 2001). Comparable classification accuracy shown in the applications and its flexibility render the MSVM a viable alternative to other classification methods.


SUPPLEMENTARY INFORMATION
http://www.stat.ohio-state.edu/~yklee/msvm.htm
6136966
Operation Shipping for Mobile File Systems
This paper addresses a bottleneck problem in mobile file systems: the propagation of updated large tiles from a weakly-connected client to its servers. It proposes an efficient mechanism called operation shipping or operation-based update propagation. In the new mechanism, the client ships the user operation that updated the large files, rather than the files themselves, across the weak network. (in contrast, existing file systems use value shipping and ship the files.) The user operation is sent to a surrogate client that is strongly connected to the servers. The surrogate replays the user operation, regenerates the files, checks whether they are identical to the originals, and, it so, sends the files to the servers on behalf of the client. Care has been taken such that the new mechanism does not compromise correctness or server scalability. For example, we show how forward error correction (FEC) can restore minor reexecution discrepancies and, thus, make operation shipping work with more applications. Operation shipping can be further classified into two types: application-transparent and application-aware. Their feasibilities and benefits have been demonstrated by the design, implementation, and evaluation of a prototype extension to the Coda File System. In our controlled experiments, operation shipping achieved substantial performance improvements-network traffic reductions from 12 times to nearly 400 times and speedups in the range of 1.4 times to nearly 50 times.
206570547
Performance evaluation of dynamic signature file methods
With rapid increase of information requirements from various application areas, there has been much research on dynamic information storage structures that effectively support insertions, deletions and updates. We evaluate the performance of the existing dynamic signature file methods such as the S-tree, Quid Filter and HS file, and provide guidelines for the most effective usage to a given operational environment. We derive analytic performance evaluation models of the storage structures based on retrieval time, storage overhead and insertion time. We also perform extensive experiments with various data distributions such as uniform, normal and exponential distributions.
14475818
Data exchange for machine shop simulation
Manufacturing simulation systems normally provide interfaces for data import and export using proprietary formats. Dependent data interfaces limit simulation applications in the manufacturing industry. This paper describes a mechanism for transferring data between a traditional database and XML files, which represent a machine shop data model developed at the National Institute of Standards and Technology (NIST). The data model is described by XML (eXtensible Markup Language) and UML (Unified Modeling Language). The data transfer mechanism is based on document object model (DOM), XML path language (XPath), and open database connectivity (ODBC) database engines. A prototype implementation is also described in this paper