The Design and Implementation of a Corporate Householding Knowledge Processor to Improve Data Quality

Madnick, Stuart E.; Wang, Thomas J.; Xian, Xiang

doi:10.1080/07421222.2003.11045772

Cited by 39 publications

(10 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These additional costs imputable to low quality data depend on multiple factors, such as the nature of the data or the type of use and users (Kim, 2002). Such costs have been reported in the literature mainly for enterprises, affirming that high quality data are fundamental factors to a company's success (Madnick et al, 2004;Haug et al, 2009;Even & Shankaranarayanan, 2009). This evidence has been recently reported also for Government Data (Zuiderwijk et al, 2015), whose disclosure policies have spread worldwide only after USA 2005 new guidelines on the Freedom of Information Act or after the presidency of the U.S.A. issued the 2013 Executive Order "Making Open and Machine Readable the New Default for Government Information".…”

Section: Introductionmentioning

confidence: 99%

Open data quality measurement framework: Definition and application to Open Government Data

Vetrò

Canova

Torchiano

et al. 2016

Government Information Quarterly

278

210

View full text Add to dashboard Cite

The diffusion of Open Government Data (OGD) in recent years kept a very fast pace. However, evidence from practitioners shows that disclosing data without proper quality control may jeopardize datasets reuse and negatively affect civic participation. Current approaches to the problem in literature lack of a comprehensive theoretical framework. Moreover, most of the evaluations concentrate on open data platforms, rather than on datasets. In this work, we address these two limitations and set up a framework of indicators to measure the quality of Open Government Data on a series of data quality dimensions at most granular level of measurement. We validated the evaluation framework by applying it to compare two cases of Italian OGD datasets: an internationally recognized good example of OGD, with centralized disclosure and extensive data quality controls, and samples of OGD from decentralized data disclosure (municipalities level), with no possibility of extensive quality controls as in the former case, hence with supposed lower quality. Starting from measurements based on the quality framework, we were able to verify the difference in quality: the measures showed a few common acquired good practices and weaknesses, and a set of discriminating factors that pertain to the type of datasets and the overall approach. On the basis of this evaluation, we also provided technical and policy guidelines to overcome the weaknesses observed in the decentralized release policy, addressing specific quality aspects.

show abstract

Section: Introductionmentioning

confidence: 99%

Open data quality measurement framework: Definition and application to Open Government Data

Vetrò

Canova

Torchiano

et al. 2016

Government Information Quarterly

278

210

View full text Add to dashboard Cite

show abstract

“…However, the most important maintenance cost is related to the consequences of not updating the PCS [7,[33][34][35]. Poor data quality has a negative impact on an organization's economic performance [36,37] and efficiency, and highquality data are crucial for its success [38][39][40][41]. Costs of corrective action [31] occur when a manufacturing company cannot satisfy customers' expectations concerning time and quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Cost of Not Maintaining a Product Configuration System

Rasmussen¹,

Myrodia²,

Hvam³

et al. 2018

IJIEM

View full text Add to dashboard Cite

This article investigates the cost implications of using a not sufficiently maintained product configuration system (PCS). A case study is conducted to investigate the financial loss due to poor data quality in products sold through a not-maintained PCS. We calculated the financial loss by comparing the quotations generated by the not-maintained PCS and the quotations for the same product when the PCS was updated. The results indicate that the company has been selling the products with a miscalculated 20% lower cost than the actual one. Comparing this financial loss to the cost required to keep the PCS up-to-date, we show that the former is significantly higher than the latter. The research concludes that the realized success and benefits of utilizing a PCS are related to its maintenance and data quality.206 Rasmussen et al. IJIEM section 3 presents the research method and introduces the case company. Section 4 presents the results and answers the research questions. Section 5 discusses the results and concludes.

show abstract

“…Structure related semantic types represent common concepts in organizational structure and entity aggregation, and thus are useful in any entity aggregation problems; the task related semantic types are specific to particular applications. The COIN reasoning process has been extended to comprehend the general semantics of the organization hierarchies that must be navigated [MWX03].…”

Section: Advances In Integrating Systems and Data Involving Complex Amentioning

confidence: 99%

Improving National and Homeland Security through Context Knowledge Representation & Reasoning Technologies

2006

View full text Add to dashboard Cite

The Design and Implementation of a Corporate Householding Knowledge Processor to Improve Data Quality

Cited by 39 publications

References 10 publications

Open data quality measurement framework: Definition and application to Open Government Data

Open data quality measurement framework: Definition and application to Open Government Data

Cost of Not Maintaining a Product Configuration System

Improving National and Homeland Security through Context Knowledge Representation & Reasoning Technologies

Contact Info

Product

Resources

About