Capturing data quality requirements for web applications by means of DQ_WebRE

2011 ◽  
Author(s):  
César Guerra-García ◽  
Ismael Caballero ◽  
Mario Piattini
Keyword(s):  
Data Quality ◽  
Web Applications ◽  
Quality Requirements

Capturing data quality requirements for web applications by means of DQ_WebRE

2012 ◽  
Vol 15 (3) ◽  
pp. 433-445 ◽  
Author(s):  
César Guerra-García ◽  
Ismael Caballero ◽  
Mario Piattini
Keyword(s):  
Data Quality ◽  
Web Applications ◽  
Quality Requirements

Methods for detecting and correcting contextual data quality problems

2021 ◽  
Vol 25 (4) ◽  
pp. 763-787
Author(s):  
Alladoumbaye Ngueilbaye ◽  
Hongzhi Wang ◽  
Daouda Ahmat Mahamat ◽  
Ibrahim A. Elgendy ◽  
Sahalu B. Junaidu
Keyword(s):  
Data Quality ◽  
Quality Evaluation ◽  
Web Applications ◽  
Support Vector ◽  
Similarity Metrics ◽  
Distributed Data ◽  
Contextual Data ◽  
Formal Taxonomy ◽  
E Learning ◽  
High Scalability

Knowledge extraction, data mining, e-learning or web applications platforms use heterogeneous and distributed data. The proliferation of these multifaceted platforms faces many challenges such as high scalability, the coexistence of complex similarity metrics, and the requirement of data quality evaluation. In this study, an extended complete formal taxonomy and some algorithms that utilize in achieving the detection and correction of contextual data quality anomalies were developed and implemented on structured data. Our methods were effective in detecting and correcting more data anomalies than existing taxonomy techniques, and also highlighted the demerit of Support Vector Machine (SVM). These proposed techniques, therefore, will be of relevance in detection and correction of errors in large contextual data (Big data).

scholarly journals Towards an adapted PHM approach: Data quality requirements methodology for fault detection applications

2021 ◽  
Vol 127 ◽  
pp. 103414
Author(s):  
N. Omri ◽  
Z. Al Masry ◽  
N. Mairot ◽  
S. Giampiccolo ◽  
N. Zerhouni
Keyword(s):  
Fault Detection ◽  
Data Quality ◽  
Quality Requirements

scholarly journals User-Oriented Approach to Data Quality Evaluation

2020 ◽  
Vol 26 (1) ◽  
pp. 107-126
Author(s):  
Anastasija Nikiforova ◽  
Janis Bicevskis ◽  
Zane Bicevska ◽  
Ivo Oditis
Keyword(s):  
Data Quality ◽  
Quality Evaluation ◽  
Open Data ◽  
Evaluation Process ◽  
Specific Model ◽  
Third Party ◽  
Quality Model ◽  
Levels Of Abstraction ◽  
Quality Requirements ◽  
Data Object

The paper proposes a new data object-driven approach to data quality evaluation. It consists of three main components: (1) a data object, (2) data quality requirements, and (3) data quality evaluation process. As data quality is of relative nature, the data object and quality requirements are (a) use-case dependent and (b) defined by the user in accordance with his needs. All three components of the presented data quality model are described using graphical Domain Specific Languages (DSLs). In accordance with Model-Driven Architecture (MDA), the data quality model is built in two steps: (1) creating a platform-independent model (PIM), and (2) converting the created PIM into a platform-specific model (PSM). The PIM comprises informal specifications of data quality. The PSM describes the implementation of a data quality model, thus making it executable, enabling data object scanning and detecting data quality defects and anomalies. The proposed approach was applied to open data sets, analysing their quality. At least 3 advantages were highlighted: (1) a graphical data quality model allows the definition of data quality by non-IT and non-data quality experts as the presented diagrams are easy to read, create and modify, (2) the data quality model allows an analysis of "third-party" data without deeper knowledge on how the data were accrued and processed, (3) the quality of the data can be described at least at two levels of abstraction - informally using natural language or formally by including executable artefacts such as SQL statements.

HF radar data quality requirements for wave measurement

2011 ◽  
Vol 58 (4) ◽  
pp. 327-336 ◽  
Author(s):  
Lucy R. Wyatt ◽  
J. Jim Green ◽  
A. Middleditch
Keyword(s):  
Data Quality ◽  
Radar Data ◽  
Hf Radar ◽  
Quality Requirements ◽  
Wave Measurement

scholarly journals An integrated system for data quality and conditions assessment for the ATLAS Tile Calorimeter

2019 ◽  
Vol 214 ◽  
pp. 01030
Author(s):  
Juraj Smiesko
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Virtual Machine ◽  
Web Applications ◽  
Web Server ◽  
Integrated System ◽  
Assessment Tools ◽  
Web Interface ◽  
Data Quality Assessment ◽  
Quality Tools

An integrated system for data quality and conditions assessment for the ATLAS Tile Calorimeter is known amongst the ATLAS Tile Calorimeter as the Tile-in-One. It is a platform for combining all of the ATLAS Tile Calorimeter offline data quality tools in one unified web interface. It achieves this by using simple main web server to serve as central hub and group of small web applications called plugins, which provide the data quality assessment tools. Every plugin runs in its own virtual machine in order to prevent interference between the plugins and also to increase stability of the platform.

Modeling Content Quality for the Web 2.0 and Follow-on Applications

2010 ◽  
pp. 371-386 ◽  
Author(s):  
Roberto Sassano ◽  
Luis Olsina ◽  
Luisa Mich
Keyword(s):  
Web Sites ◽  
Web Application ◽  
Web Applications ◽  
Integrated Approach ◽  
Web Engineering ◽  
Quality Requirements ◽  
Content Quality ◽  
The Web ◽  
Quality In Use

The consistent modeling of quality requirements for Web sites and applications at different stages of the life cycle is still a challenge to most Web engineering researchers and practitioners. In the present chapter, we propose an integrated approach to specify quality requirements to Web sites and applications. By extending the ISO 9126-1 quality views characteristics, we discuss how to model internal, external quality, and quality in use views taking into account not only the software features, but also the own characteristics of Web applications. Particularly, we thoroughly analyze the modeling of the content characteristic for evaluating the quality of information–so critical for the whole Web application eras. The resulting model represents a first step towards a multi-dimensional integrated approach to evaluate Web sites at different lifecycle stages.

scholarly journals Evaluating the Quality of Social Web Applications Using the LSP Method

2020 ◽  
Vol 15 (10) ◽  
pp. 55
Author(s):  
Tihomir Orehovački
Keyword(s):  
Web Applications ◽  
Aggregation Operators ◽  
Evaluation Procedure ◽  
Social Web ◽  
Quality Model ◽  
Quality Requirements ◽  
Performance Variables ◽  
Single Score

Quality is an essential determinant of the success of every type of software and social Web applications are not an exception. It is therefore of great importance that the examination of the degree to which social Web applications meet predefined requirements related to particular facets of quality is performed effectively and frequently. With an objective to facilitate evaluation procedure and enable comparison of social Web applications at all levels of the quality model, we initiated a research into development of a methodology that will aggregate quality requirements into a single score. The work presented in this paper draws on the employment of the logic scoring of preference (LSP) method and outlines only some parts of the aforementioned methodology. After identifying quality attributes that constitute the requirement tree, elementary criteria for both objective and subjective performance variables were introduced. As a follow up, field experts were included in the study in order to determine weights of performance variables within particular performance subsystem. Finally, the appropriate logic aggregation operators were selected based on the relevance of performance variables

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