Modern Project Management

(ISSN: 2317-3963)

An Overview of Project Data for Integrated Project Management and Control

Mario Vanhoucke
Faculty of Economics and Business Administration, Ghent University; Belgium Technology and Operations Management Area, Vlerick Business School, Ghent, Belgium; University College London, United Kingdom Belgium
José Coelho
Universidade Aberta - Lisbon, Portugal INESC – Technology and Science - Porto, Portugal Portugal
José Coelho
Universidade Aberta - Lisbon, Portugal INESC – Technology and Science - Porto, Portugal Portugal
Jordy Batselier
Ghent University - Belgium Belgium


In this paper, an overview is given of the project data instances available in the literature to carry out academic research in the field of integrated project management and control. This research field aims at integrating static planning methods and risk analyses with dynamic project control methodologies using the state-of-the-art knowledge from literature and the best practices from the professional project management discipline. Various subtopics of this challenging discipline have been investigated from different angles, each time using project data available in literature, obtained from project data generators or based on a sample of empirical case studies. This paper gives an overall overview of the wide variety of project data that are available and are used in various research publications. It will be shown how the combination of artificial data and empirical data leads to improved knowledge on and deeper insights into the structure and characteristics of projects useful for academic research and professional use. While the artificial data can be best used to test novel ideas under a strict design in a controlled academic environment, empirical data can serve as the necessary validation step to translate the academic research results into practical ideas, aiming at narrowing the bridge between the theoretical knowledge and practical relevance. A summary of the available project data discussed in this paper can be downloaded from

Keywords: Project Data, Dynamic Scheduling, Monte Carlo Simulation, Baseline Scheduling, Schedule Risk Analysis, Project Control.



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