Modular Environmental Monitoring Ontology (MEMOn)
Last update: 14 december 2018
version : 1.1
Main author : Maroua Masmoudi, ENSI, University of Manouba, Tunisie.
ENIT, University of Toulouse, France.
Contributing authors : Mohamed Hedi Karray, ENIT, University of Toulouse, France.
Sana Ben Abdallah Ben Lamine, ENSI, University of Manouba, Tunisie.
Hajer Baazaoui Zghal, ENSI, University of Manouba, Tunisie.
Bernard Archimede, ENIT, University of Toulouse, France.
This research was funded by the PHC-Utique Project, PREDICA, number: 17G-1122, financed by Campus France and the Tunisian MESRS.
Abstract
Earth observation (EO) systems play a significant role in the environment’s monitoring and the prediction of natural disasters. These systems generate a huge amount of heterogeneous data stored in different formats. The exploitation of this data is still limited while, in most cases, data are not linked and sources are not interoperable. Hence, data cannot be exploited as a global interoperable knowledge graph to have a deeper analyzes of environmental phenomena. Ontology, as a knowledge representation formalism, is a promising solution for the semantic interoperability between this data. In this work, we present a modular ontology for environmental monitoring developed based on an original agile methodology. The so-called MEMOn (Modular Environmental Monitoring Ontology) aims to support semantic interoperability, data integration and linking of heterogeneous data collected through a variety of observation techniques and systems. We also present a real use case studies to show the usefulness of the proposed ontology.
Introduction
MEMOn is based on the Basic Formal Ontology (BFO). It incorporates also reference ontologies such as Common Core Ontologies (CCO), Relation ontology (RO ), and includes terms reused from Semantic Sensor Ontology (SSN) and Environment ontology (ENVO) .
MEMOn ontology consists of a set of ontological modules covering the subdomains of environmental monitoring. So, our modules are decomposed according to contexts needed in environmental monitoring (such as temporal context, Observation & Measurement context, geospatial context). Thus, MEMOn consists of 8 main modules, namely disaster module, observation and measurement module, infrastructure module, temporal module, geospatial module, sensor and sensing module, environmental processes module and environmental material module.
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Observation&Measurement Module
This module is concerned with describing how observations are related to events and to measurements. Observation is defined as “An act of observing a property or a phenomenon” in order to produce an estimate of the value of the property. The goal of an observation might be to measure or otherwise determine the value of a property.
View Observation&Measurement Module
To see or download Observation&Measurement module in OWL format, click here.
Sensor&Sensing Module
Sensing System Module describes various types of sensors and sensing observation systems (such as satellites). A sensing System is an entity capable of observing a property and transmitting a resulting value. A ‘sensing System’ can be in-situ sensor, a satellite or a system which have multiple sensors/satellites as parts.
To see or download Sensor&Sensing module in OWL format, click here.
Geospatial Module
This module addresses the spatial aspect by including environmental features (e.g. landforms, ecosystems, marine features), spatial regions (such as geopolitical regions, continents) and relationships among features and places to define spatial context. To build this module we reuse geospatial ontology from CCO.
Natural disaster Module
This module includes natural disasters. Natural disasters are divided in four categories; climatological disaster, geophysical disaster, hydrological disaster and meteorological disaster.
To see or download Disaster module in OWL format, click here.
Environmental Process Module
Environmental process module include entities that occur and develop in time, unfolds in successive phases and depends on some material entity”. For this module we reused ENVO terms to define environmental processes. These processes include climatological processes, hydrological processes, geographical processes, geophysical processes, material transport processes and material transformation processes. Environmental processes classes share relationships with each other such as “preceded by, caused by, happens during”.
View Environmental Process Module
To see or download Environmental Process module in OWL format, click here.
Environmental Material Module
Environmental material module include entities which forms the medium or part of the medium of an environmental system. All classes of this module are to be understood as being composed primarily of the named entity. For example, "water" is to be understood as "environmental material composed primarly of some "water".
The relation between environmental monitoring and environmental materials is obvious. Environmental material quality (such as water quality), or environmental material existence (such as fume) are observations detected by environmental monitoring techniques.
To build this module, we reuse ENVo ontology.
View Environmental Material Module
To see or download Environmental Material module in OWL format, click here.
Infrastructure Module
Infrastructure objects which are deployed in a specific location where certain environmental process occurs, could participate in environmental hazard factors. This module include these objects. Infrastructure objects are divided in two types: hydraulic and transportiong infrastructures. To build this module we reuse Artifact Ontology (AO) from CCO.
To see or download Infrastructure module in OWL format, click here.
Temporal Module
This module describe temporal information. Temporal information is important in environmental monitoring applications. For example, the date is always part of an occurred disaster. Environmental events in the world occur at specific times and usually have a finite duration. To build this module we reuse Time Ontology from CCO.
To see or download Temporal module in OWL format, click here.