A Knowledge Ecosystem for the Food, Energy, and Water System
| Autor: | Rao, Praveen, Katib, Anas, Barron, Daniel E. Lopez |
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| Rok vydání: | 2016 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | Food, energy, and water (FEW) are key resources to sustain human life and economic growth. There is an increasing stress on these interconnected resources due to population growth, natural disasters, and human activities. New research is necessary to foster more efficient, more secure, and safer use of FEW resources in the U.S. and globally. In this position paper, we present the idea of a knowledge ecosystem for enabling the semantic data integration of heterogeneous datasets in the FEW system to promote knowledge discovery and superior decision making through semantic reasoning. Rich, diverse datasets published by U.S. federal agencies will be utilized. Our knowledge ecosystem will build on Semantic Web technologies and advances in statistical relational learning to (a) represent, integrate, and harmonize diverse data sources and (b) perform ontology-based reasoning to discover actionable insights from FEW datasets. Comment: KDD 2016 Workshop on Data Science for Food, Energy and Water, Aug 13-17, 2016, San Francisco, CA |
| Databáze: | arXiv |
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