Information: A Crucial Resource for Resource Management

Material Flow Analysis (MFA) is a central tool of resources management. Although data can be considered a crucial resource for resource management, there is no common understanding on what MFA data is, how it contributes to MFA results, and how it can be discussed and communicated. This study contributes to this issue by proposing a terminology for information in Material Flow Analysis, and indicating further research steps towards consistent data base analysis and data quality assessment. The approaches of this study are illustrated by examples of two nation-wide MFA case studies on metals and phosphorus. The findings can, among others, contribute to increased MFA system understanding, database communication and data quality assessment.

Material Flow Analysis (MFA) is a crucial decision support tool in resource and waste management. The freeware STAN (Cencic and Rechberger 2008) has proven to be a practicable and flexible tool for MFAs, that allows to consider uncertainties, and provides practicable functions not only for visualization, but also for modeling of material flows and stocks. Elaborate studies of anthropogenic cycles have often revealed information that would remain unknown without sophisticated system studies and extensive data search (Chen and Graedel 2012). In MFA, cross-disciplinary data from heterogeneous sources such as official trade statistics, scientific findings and consumer behavior studies, are combined. However, there is often no data or limited data available for MFA which is, among others, because relevant data may be confidential, lost, highly aggregated or real-world phenomena are simply too complex to be measured. On the other hand, today the possibilities to access and communicate information from various sources are immense, and 'it is sometimes said that we now have more and more information that we know less and less about†(Madnick and Zhu 2006). This is often due to improperly understood or used data semantics and limited context knowledge (Madnick and Zhu 2006). Although there is an approach for the assessment of data uncertainties in MFA that was applied several times and further developed (Hedbrant and Sörme 2001), there remains a fundamental question: What data in MFA actually is, how it can be perceived, understood and assessed. In other disciplines, mainly social sciences, such 'theories of data†have been subject to research since many years (Bichlbauer 1989), but are still lacking in MFA.
 
 
Authors:
Dipl. Geoökol. Oliver Schwab
Dipl.-Ing. David Laner
Professor Dipl.-Ing. Dr. Helmut Rechberger



Copyright: © Deutsche Gesellschaft für Abfallwirtschaft e.V. (DGAW)
Quelle: 4. Wissenschaftskongress März 2014 - Münster (März 2014)
Seiten: 6
Preis: € 3,00
Autor: Prof. Dr. David Laner
Professor Dipl.-Ing. Dr. Helmut Rechberger
 
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