RT Journal Article
T1 A conceptual data modeling framework with four levels of abstraction for environmental information
A1 Martínez, David
A1 Po, Laura
A1 Trillo-Lado, Raquel
A1 Ríos Viqueira, José Ramón
K1 Conceptual data modeling
K1 Environmental data
K1 Data management
K1 Meteorological data
K1 Oceanographic data
K1 Air quality data
K1 Data integration
AB Environmental data generated by observation infrastructures and models is widely heterogeneous in both structure and semantics. The design and implementation of an ad hoc data model for each new dataset is costly and creates barriers for data integration. On the other hand, designing a single data model that supports any kind of environmental data has shown to be a complex task, and the resulting tools do not provide the required efficiency. In this paper, a new data modeling framework is proposed that enables the reuse of generic structures among different application domains and specific applications. The framework considers four levels of abstraction for the data models. Levels 1 and 2 provide general data model structures for environmental data, based on those defined by the Observations and Measurements (O&M) standard of the Open Geospatial Consortium (OGC). Level 3 incorporates generic data models for different application areas, whereas specific application models are designed at Level 4, reusing structures of the previous levels. Various use cases were implemented to illustrate the capabilities of the framework. A performance evaluation using six datasets of three different use cases has shown that the query response times achieved over the structures of Level 4 are very good compared to both ad hoc models and to a direct implementation of O&M in a Sensor Observation Service (SOS) tool. A qualitative evaluation shows that the framework fulfills a collection of general requirements not supported by any other existing solution.
PB Elsevier
SN 1364-8152
YR 2025
FD 2025-01
LK https://hdl.handle.net/10347/38145
UL https://hdl.handle.net/10347/38145
LA eng
NO Martínez, M., Po, L., Trillo-Lado, R., R. Viqueira, J. R. (2025). A conceptual data modeling framework with four levels of abstraction for environmental information. “Environmental Modelling & Software”, vol 183, https://doi.org/10.1016/j.envsoft.2024.106248.
NO This work was partially supported by the following projects. TRAFAIR project (2017-EU-IA-0167), co-financed by the Connecting Europe Facility of the European Union. Galicia Marine Science programme, which is part of the Complementary Science Plans for Marine Science of Ministerio de Ciencia, Innovación   Universidades included in the Recovery, Transformation and Resilience Plan (PRTR-C17.I1), funded through Xunta de Galicia with NextGenerationEU and the European Maritime Fisheries and Aquaculture Funds. EarthDL-USC (PID2022-141027NB-C22) and NEAT-AMBIENCE (PID2020-113037RB-I00) projects, funded by Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación , through the national plan of scientific and technical research and innovation 2021–2023.
DS Minerva
RD 24 abr 2026