A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
People Manipulate Objects (but Cultivate Fields): Beyond the Raster-Vector Debate in GIS
Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
AI Magazine
A Generic Algorithmic Framework for Aggregation of Spatio-Temporal Data
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Spatiotemporal Aggregate Computation: A Survey
IEEE Transactions on Knowledge and Data Engineering
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ACM SIGMOD Record
Environmental Modelling & Software
A survey on summarizability issues in multidimensional modeling
Data & Knowledge Engineering
Ontologies and summarizability in OLAP
Proceedings of the 2010 ACM Symposium on Applied Computing
INTAMAP: The design and implementation of an interoperable automated interpolation web service
Computers & Geosciences
A conceptual framework for managing very diverse data for complex, interdisciplinary science
Journal of Information Science
Spatio-temporal aggregation of European air quality observations in the Sensor Web
Computers & Geosciences
Integrated environmental modeling: A vision and roadmap for the future
Environmental Modelling & Software
Managing uncertainty in integrated environmental modelling: The UncertWeb framework
Environmental Modelling & Software
'Integronsters', integral and integrated modeling
Environmental Modelling & Software
Ontology paper: The SSN ontology of the W3C semantic sensor network incubator group
Web Semantics: Science, Services and Agents on the World Wide Web
Position paper: Characterising performance of environmental models
Environmental Modelling & Software
A temporal GIS for field based environmental modeling
Environmental Modelling & Software
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The appropriateness of spatial prediction methods such as Kriging, or aggregation methods such as summing observation values over an area, is currently judged by domain experts using their knowledge and expertise. In order to provide support from information systems for automatically discouraging or proposing prediction or aggregation methods for a dataset, expert knowledge needs to be formalized. This involves, in particular, knowledge about phenomena represented by data and models, as well as about underlying procedures. In this paper, we introduce a novel notion of meaningfulness of prediction and aggregation. To this end, we present a formal theory about spatio-temporal variable types, observation procedures, as well as interpolation and aggregation procedures relevant in Spatial Statistics. Meaningfulness is defined as correspondence between functions and data sets, the former representing data generation procedures such as observation and prediction. Comparison is based on semantic reference systems, which are types of potential outputs of a procedure. The theory is implemented in higher-order logic (HOL), and theorems about meaningfulness are proved in the semi-automated prover Isabelle. The type system of our theory is available as a Web Ontology Language (OWL) pattern for use in the Semantic Web. In addition, we show how to implement a data-model recommender system in the statistics tool environment R. We consider our theory groundwork to automate semantic interoperability of data and models.