Oliver Schwab
Biographic Data
| ID | 8953546 |
|---|---|
| NAME | Oliver Schwab |
| GIVEN NAMES | Oliver |
| FAMILY NAME | Schwab |
| SIGNATURE | SCHWAB O |
| AFFILIATIONS | TU Wien |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 1 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2018 |
| H-INDEX | 0 |
Information Content, Complexity, and Uncertainty in Material Flow Analysis
Material Flow Analysis (MFA) is a useful method for modeling, understanding, and optimizing sociometabolic systems. Among others, MFAs can be distinguished by two general system properties: First, they differ in their complexity, which depends on system structure and size. Second, they differ in their inherent uncertainty, which arises from limited data quality. In this article, uncertainty and complexity in MFA are approached from a systems pers…
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Quantitative Evaluation of Data Quality in Regional Material Flow Analysis
A method for quantitative evaluation of data quality in regional material flow analysis (MFA) is presented. The principal idea is that data quality is a multidimensional problem that cannot be judged by individual characteristics such as the data source, given that data from official statistics may not be per se of good quality and expert estimations may not be per se of bad quality, respectively. It appears that MFA data are never totally accura…
A Data Characterization Framework for Material Flow Analysis
The validity of material flow analyses (MFAs) depends on the available information base, that is, the quality and quantity of available data. MFA data are cross‐disciplinary, can have varying formats and qualities, and originate from heterogeneous sources, such as official statistics, scientific models, or expert estimations. Statistical methods for data evaluation are most often inadequate, because MFA data are typically isolated values rather t…
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Starke Kommunen – wirksame Verwaltung
Starke Kommunen - Wirksame Verwaltung
Quantitative Evaluation of Data Quality in Regional Material Flow Analysis
A method for quantitative evaluation of data quality in regional material flow analysis (MFA) is presented. The principal idea is that data quality is a multidimensional problem that cannot be judged by individual characteristics such as the data source, given that data from official statistics may not be per se of good quality and expert estimations may not be per se of bad quality, respectively. It appears that MFA data are never totally accura…
A Data Characterization Framework for Material Flow Analysis
The validity of material flow analyses (MFAs) depends on the available information base, that is, the quality and quantity of available data. MFA data are cross‐disciplinary, can have varying formats and qualities, and originate from heterogeneous sources, such as official statistics, scientific models, or expert estimations. Statistical methods for data evaluation are most often inadequate, because MFA data are typically isolated values rather t…
Information Content, Complexity, and Uncertainty in Material Flow Analysis
Material Flow Analysis (MFA) is a useful method for modeling, understanding, and optimizing sociometabolic systems. Among others, MFAs can be distinguished by two general system properties: First, they differ in their complexity, which depends on system structure and size. Second, they differ in their inherent uncertainty, which arises from limited data quality. In this article, uncertainty and complexity in MFA are approached from a systems pers…
Computer Science (3 works) · Data mining (3 works) · Engineering (3 works) · Data quality (2 works) · Environmental Impact and Sustainability (2 works) · Extraction and Separation Processes (2 works) · Information flow (2 works) · Material flow analysis (2 works) · Mathematics (2 works) · A priori and a posteriori (1 work)