Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Dealing with complexity: an introduction to the theory & applications of systemsscience
Dealing with complexity: an introduction to the theory & applications of systemsscience
Object-oriented software metrics: a practical guide
Object-oriented software metrics: a practical guide
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
A methodological framework for data warehouse design
Proceedings of the 1st ACM international workshop on Data warehousing and OLAP
Investigating quality factors in object-oriented designs: an industrial case study
Proceedings of the 21st international conference on Software engineering
starER: a conceptual model for data warehouse design
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Building Knowledge through Families of Experiments
IEEE Transactions on Software Engineering
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Principles of survey research: part 1: turning lemons into lemonade
ACM SIGSOFT Software Engineering Notes
A Framework of Software Measurement
A Framework of Software Measurement
Software Metrics: A Rigorous Approach
Software Metrics: A Rigorous Approach
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Object Oriented Design Measurement
Object Oriented Design Measurement
Fundamentals of Data Warehouses
Fundamentals of Data Warehouses
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
A Methodology for the Design and Transformation of Conceptual Schemas
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Using Metrics to Predict OO Information Systems Maintainability
CAiSE '01 Proceedings of the 13th International Conference on Advanced Information Systems Engineering
YAM2 (Yet Another Multidimensional Model): An Extension of UML
IDEAS '02 Proceedings of the 2002 International Symposium on Database Engineering & Applications
Normal Forms for Multidimensional Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Extending the UML for Multidimensional Modeling
UML '02 Proceedings of the 5th International Conference on The Unified Modeling Language
Metrics for Evaluating the Quality of Entity Relationship Models
ER '98 Proceedings of the 17th International Conference on Conceptual Modeling
Design and Analysis of Quality Information for Data Warehouses
ER '98 Proceedings of the 17th International Conference on Conceptual Modeling
Extending the E/R Model for the Multidimensional Paradigm
ER '98 Proceedings of the Workshops on Data Warehousing and Data Mining: Advances in Database Technologies
Architecture of Systems Problem Solving
Architecture of Systems Problem Solving
Finding Your Way through Multidimensional Data Models
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
OOA Metrics for the Unified Modeling Language
CSMR '98 Proceedings of the 2nd Euromicro Conference on Software Maintenance and Reengineering ( CSMR'98)
Multidimensional normal forms for data warehouse design
Information Systems
Building the Data Warehouse
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Basics of Software Engineering Experimentation
Basics of Software Engineering Experimentation
A Methodology for Collecting Valid Software Engineering Data
IEEE Transactions on Software Engineering
A UML profile for the conceptual modelling of data-mining with time-series in data warehouses
Information and Software Technology
A comprehensive approach to data warehouse testing
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Information and Software Technology
Quality metrics for conceptual models for data warehouse focusing on dimension hierarchies
ACM SIGSOFT Software Engineering Notes
Quality-oriented requirements engineering for a data warehouse
ACM SIGSOFT Software Engineering Notes
A modularization proposal for goal-oriented analysis of data warehouses using i-star
ER'11 Proceedings of the 30th international conference on Conceptual modeling
Hybrid methodology for data warehouse conceptual design by UML schemas
Information and Software Technology
Complexity metric for multidimensional models for data warehouse
Proceedings of the CUBE International Information Technology Conference
Understanding understandability of conceptual models --- what are we actually talking about?
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
International Journal of Data Warehousing and Mining
Journal of Database Management
Effective data warehouse for information delivery: a literature survey and classification
International Journal of Networking and Virtual Organisations
Adding semantic modules to improve goal-oriented analysis of data warehouses using I-star
Journal of Systems and Software
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Due to the principal role of Data warehouses (DW) in making strategy decisions, data warehouse quality is crucial for organizations. Therefore, we should use methods, models, techniques and tools to help us in designing and maintaining high quality DWs. In the last years, there have been several approaches to design DWs from the conceptual, logical and physical perspectives. However, from our point of view, none of them provides a set of empirically validated metrics (objective indicators) to help the designer in accomplishing an outstanding model that guarantees the quality of the DW. In this paper, we firstly summarise the set of metrics we have defined to measure the understandability (a quality subcharacteristic) of conceptual models for DWs, and present their theoretical validation to assure their correct definition. Then, we focus on deeply describing the empirical validation process we have carried out through a family of experiments performed by students, professionals and experts in DWs. This family of experiments is a very important aspect in the process of validating metrics as it is widely accepted that only after performing a family of experiments, it is possible to build up the cumulative knowledge to extract useful measurement conclusions to be applied in practice. Our whole empirical process showed us that several of the proposed metrics seems to be practical indicators of the understandability of conceptual models for DWs.