Zoltan Kazi

Performance indicators in software project monitoring: Balanced scorecard approach

Balanced scorecard is one of most used methodologies for performance measurement in enterprises and non-profit organizations. It presents a general framework that has been applied more precisely by many scientists and practitioners. It has been adapted to particular performance measurement systems. These monitoring systems are based on collecting data and analysis of these data. This paper presents overview of implementing balanced scorecard in IT project management. Framework for software project success monitoring, based on PRINCE2 methodology and balanced scorecard is proposed. Key performance indicators as measures to be performed upon data collected during software project implementation are defined. This way, analytics to be performed upon data according to specified key performance indicators, needed for decision support is enabled.

Approach for Synonyms Detection in Conceptual Data Model

Detection of synonyms in data modeling is considered as a significant problem, especially within the semantic evaluation of a conceptual data model. This paper presents an approach for synonyms detection in a system for conceptual data model semantic evaluation. It is based on automated reasoning in ontology mapping with conceptual data model with tool that formalizes ontology and conceptual data model and merges them with a set of reasoning rules. Reasoning was done with Prolog system. These rules are created for ontology–toconceptual data model mapping, as well for synonyms extraction. Examples of testing reasoning rules are also shown in the paper.

Integration of conceptual data modeling methods: Higher education experiences

One of the most important phases in information system development is data modeling. In higher education and in professional environment, the basic data models are ER model, relational model and object oriented model, i.e. class diagram. Since conceptual modeling is crucial data modeling activity, special concern on methods for conceptual modeling is given in this paper. Case study shows that application of separate conceptual data modeling methods produce different and incomplete models. This leads to the conclusion that it is important to use integration of these methods and apply them within the information system development process. Educational experiences of applying this approach at University of Novi Sad, Technical faculty “Mihajlo Pupin” in Zrenjanin are presented as description of class exercises and exams results.

Using automated reasoning system for data model correctness analysis

Data modeling is one of the most important activities in the process of information systems development which is based on domain knowledge in specific area. This paper presents a system for analyzing data model correctness from both syntax and semantic aspect. The system is based on using ontology for domain knowledge representation, transformation of data models and ontology to predicate logic form and their integration with data model quality rules. All components of the system are integrated by using XML form of their results. They create an input for an automated reasoning system, that provide answers regarding data model correctness.