Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Everglades R-EMAP 2005

The Everglades R-EMAP project for year 2005 produced large quantities of data collected at 232 sampling sites. Data collection and analysis is an on-going long-term activity conducted by scientists of different disciplines at irregular intervals of several years. The data sets collected for 2005 include bio-geo-chemical (including mercury and hydro period), fish, invertebrate, periphyton, and plant data. Each sampling site is associated with a location, a description of the site to provide a general overview and photographs to provide a pictorial impression. The Geographic Information Systems and Remote Sensing Center(GISRSC) at Florida International University (FIU) has designed and implemented an enterprise database for long-term storage of the project�s data in a central repository, providing the framework of data storage for the continuity of future sampling campaigns and allowing integration of new sample data as it becomes available. In addition GISRSC provides this interactive web application for easy, quick and effective retrieval and visualization of that data.