Call for papers
A number of opportunities for cross-fertilization between the fields of ICT Quality and Business Intelligence/Data Mining (BI/DM) have been identified in recent years: BI/DM can be used to support better Quality processes in ICT, particularly software and systems development; and (ICT) Quality methodologies can be used to enable more successful BI/DM projects.
As ICT Quality processes become increasingly more complex, and have (the opportunity) to deal with increasing amounts of data (in software repositories, project management repositories, diagnostics logs, etc.), they also become harder to manage. BI technologies, including data warehousing, OLAP and data mining can help to address that problem. However, this domain poses important challenges to BI, particularly the diverse and complex nature of the data, which may include text, sequences and graphs, frequently in combination.
In BI/DM, on the other hand, the quality of the information delivered – the right information at the right time – as well as the quality of the delivery process are crucial for the decision-making process. While some Quality-related issues have been an extensively investigated issue in some of the sub-fields of BI such as evaluation of data mining results, it has received less attention in others, most notably concerning the assessment of BI methodologies. Therefore, it is expected that important improvements can be achieved by adopting and adapting ICT Quality approaches in this field.
We intend to bring together these two communities and therefore, we seek contributions on the application of BI/DM on Quality processes as well as on the impact of Quality aspects in the development process of BI/DM solutions.
Suggested topics of interest include, but are not restricted to:
- Application of BI technologies on ICT Quality processes
- Adaptation of BI technologies to deal with specific issues of ICT Quality processes (e.g., complex types of data)
- Evaluation of the Quality Assurance Activities and Practices in the context of the development of BI systems
- Quality metrics for BI Project Management
- Agile methodologies for Data Warehouse design
- Data quality approaches in Data Warehousing
- Quality issues in Data Mining and Statistical Analysis
- The impact of quality in real-time BI systems
- Empirical evaluation on evidence concerning the effect of BI quality approaches in the decision making process
Petr BerkaUniversity of Economics, Prague, Czech Republic
Orlando BeloUniversity of Minho, Portugal
Helena GalhardasTechnical University of Lisbon/INESC-ID, Portugal
Matjaz KukarUniversity of Ljubljana, Slovenia
Stefano RizziUniversity of Bologna, Italy
Hongyu ZhangTsinghua University, China