The process of identifying the attributes and relationships considered in an ontology is a complex task because there are many factors involved in the deterioration of environmental quality, the diversity of sources and data dispersion. This work presents an ontology that integrates the data required by an Environmental Quality Synoptic System (EQSS), which to date scatters in different Internet sites and concentrates by different agencies for example INEGI, CONABIO, SEMARNAT, CNA, among others. The methodology process consists of the collection of environmental information in Mexico through the application of computational techniques resulting ontology with environmental knowledge that will be processed by the system EQSS. Among the main advantages is than the selection and structure of information allow the automated generation of results in an environmental statement. The ontology proposal is based on knowledge of EQSS system that is based on the architecture of expert systems and through this important information for decision-making in regard to environmental quality and interaction with Geographic Information System (GIS) is obtained.
The constant evolution of technology has enabled us to manipulate information in the ways different from the past when it was only carried out manually and with a large time investment. Similarly, it is also possible to perform processes that previously require a lot of human resources, such as statistical calculations, reports, and graphs. Currently there is a lot of environmental information from different sources, such as documents, databases and files with geographic information, satellite images, aerial photographs, maps, among others. These sets of data can provide important information on qualitative and quantitative characteristics inherent to the environment and its relation to the relative’s capacity to meet the needs of people and ecosystems [
Hence, the objective of this research is to present a methodology for the design of an environmental ontology and its application in the Environmental Quality Synoptic System (EQSS). Given the complexity of the collection of environmental information and its impact on decision-making in environmental public policy, it is required to have a mechanism capable of integrating data and relations between them allowing form a knowledge base EQSS. This architecture operates according to the methodology of the art Rapid Evaluation of Sources of Environmental Contamination (ERFCA by its acronym in Spanish) [
As described within the requirements to allow the assessment of environmental quality in a given study area, it is necessary to have a mechanism to integrate useful information. The objective of this research is to present the methodology required to design an environmental ontology and its application in a Web system for estimating environmental quality. The term ontology is used in systems of knowledge representation to denote a knowledge model that represents a particular domain of interest. A knowledge domain represented by formally in a conceptualization: the objects, concepts and other entities that presumed to exist in some area of interest and the relationships between them. In the Semantic Web, ontologies are a key component for knowledge modeling through the interoperability between different systems and reuse of existing knowledge in new systems [
The proposed methodology integrates provided by Noy and McGuinness [
Defining the scope of environmental ontology. The goal of the ontology and its functionality within the Web evaluation system of environmental quality, for it must analyze existing ontologies and technology that has been used for implementation defined. At this stage the field of environmental ontology is determined, i.e. the set of information that will be modeling and computational tools necessary for its creation.
Ontology design from the input and expected output. The structure of the ontology defined by identifying the attributes, relationships based on the information obtained in the previous step. The structure of the bases of official environmental data analyzed, identifying and relating each of the entities and their attributes with the concepts defined in the ontology.
Integration of ontology instances proposals. Mechanism is defined to feed the required data in the ontology, this process is called mapping instances and unifies the different data sets and integrate them into the ontology.
Implementing search engine. The design and implementation of the interface and modules required searching for information about the ontology performed, this process involves the mapping of instances, the process of search and display process for displaying the data required by the user.
Retrieving and displaying data. Function responsible for formatting oftenest consultation data ontology implemented. This output format is an executive report, called Cabinet Study, which may include graphic and thematic maps if it selected in the user interface EQSS system that aims to provide the assessment of environmental impact consistent material for decision-making.
The design of the ontology based on client-server architecture, as shown in
access information through a Web browser. For the import of databases has been used MYSQL 5.6.14 and SQL Server 2008 Language program for Web user interfaces is PHP 5.5.6. The ontology was developed in language OWL (Web Ontology Language) based on the RDF/XML syntax using the Protégé tool, which is a tool for developing ontologies created by Stanford University, which aims to further facilitate the construction is able to display all the knowledge of an area for later analysis.
Regarding the definition of domain ontology, has made a previous work to identify the domain and scope of the ontology by analyzing the information required by the technical ERFCA mainly covering the following criteria:
1) Study area.
2) Industrial pollutants and non-industrial sources.
3) Classification of pollution sources according to United Nations, UN.
4) Pollutants and factors associated with each of the categories described in the UN classification.
The study area, pollutant sources, UN classification, Environmental Statement, indicators primarily, and from this information and based on propositional logic entities identified a taxonomy has been modeled from a hierarchical graph to represent a semantic network mainly order to establish the classes. The relationship types, properties and allow ontology know what the inheritance relationships that exist through their predecessors in the graph are.
Instance mapping is based on the D2RQ [
・ The National Commission for the Knowledge and Use of Biodiversity (CONABIO by its acronym in Spanish) [
・ The Secretariat of Environment and Natural Resources (SEMARNAT by its acronym in Spanish) [
・ The National Institute of Statistics, Geography and Informatics (INEGI by its acronym in Spanish) [
・ The National Water Commission (CNA by its acronym in Spanish) [
・ The Federal Attorney for Environmental Protection (PROFEPA by its acronym in Spanish) [
It has been decided to consider primarily stores data from INEGI and SEMARNAT. All information collected downloaded directly from its official website, considering data, images and maps related to the ontology entities. The structure that uses each of the selected data sources and data base ERFCA itself is variable in
Once concentrated information relevant to the ontology we proceed to generate instances (
The information obtained in the first step follows the principle of relational databases so it is necessary to establish a correspondence between the information obtained and the ontology. The following figure shows the tables presented with information extracted from the BDs of INEGI and SEMARNAT, with his environmental variable to which they belong.
The goal of integration is to provide a unified database with different structures through independent ontology access avoiding duplication and lack of updating information. The unified access means that once connected the ontology to the external data store, through a user interface, access to a set of heterogeneous data that are independent to each other, but both are part of the same domain. In
Firstly, it is set to a file using the syntax D2RQ the relationship between OWL ontology schema and relational database. Database, D2RQ: jdbcDSN, D2RQ: ClassMap and D2RQ: PropertyBridge For this, two basic structures D2RQ language D2RQ are used. Below in
The ClassMap structure represents the group of OWL ontology classes and through the sentence, map database is linked with some data of ontology. The D2RQ property: uriPattern Tabla. Columna notation specifies the schema within the database and so on set during the mapping information.
As a result of mapping instances a mapping file is generated from a declarative language that describes relationship between RDFS or OWL ontologies with a relational database through D2RQ. From this file the D2RQ platform manages to transform a database on a network. By mapping data, the user is able to request consultation with the ontology. In EQSS UI, the user selects the study area, comprising one or more municipalities in
Mexico, and is generated through a report called ontology Baseline or Environmental Statement, this process is shown in
The Environmental Statement is generated from an interface and modeled by an ontology is a critical tool necessary in the process of assessing environmental quality territorial regulation, planning and management, development of environmental management plans, waste management, vulnerability analysis, among others [
The studies in the area of Artificial Intelligence since 1960 [
generating services offer a rich and modern knowledge for modeling providing services and manage terminology in any subject contextual framework. The ontology proposed based on knowledge of EQSS, which requires a set of related data-dos with physical-natural, mainly social and economic information. The information obtained from data sources in Mexico and government agencies are working to ensure that access to the data is in real time through the available Web services. Within perspectives is implementing a Web Service based GeoData semantic mapping, which allows to the user modeled in accordance with the needs of the problem to be solved, such as prediction models fire, requiring the creation and integration of geospatial data more related climate, human activities and flammability of specific regions [
Within the assessment, methods in the field of semantic technologies are found and the ontologies as the knowledge of storage model in the area of environment are dynamic, collaborative and iterative. This process needs to be understood, evaluated and managed between domain experts and an automated manner. Progress in this direction allows us to expand the existing arsenal of techniques for analyzing environmental data ontology evaluation towards more holistic approaches. With the emergence of new devices, new technologies and new services, the GIS applications are really very important and are used in various fields such as public policy instruments which can model the dispersion of pollutants.
To determine the system requirements, the process and outputs of ERFCA technique, the data entry system is related to the study area to assess, while the expected outputs must be in terms of media (air, water, soil), sectorial (industrial, not industrial) and source (mobile or not mobile). The environment ontology proposed based on the user interface EQSS can produce information for decision-making concerning environmental quality and is considered to interact with Geographic Information Systems (GIS).
The authors thank the Improvement Professorate Program (PROMEP for its acronym in Spanish) for the support given to project number: New Teachers Full Time Support for PROMEP/103.5/13/6715.
René Bernardo ElíasCabrera-Cruz,ErikaAlarcón-Ruiz,Julio CésarRolón-Aguilar,Salvador W.Nava-Díaz,Elena MaríaOtazo-Sánchez,Ricardo PérezAviléz, (2015) Developing Ontology Systems as a Base of an Environmental Quality Management Model in México. Journal of Environmental Protection,06,1084-1093. doi: 10.4236/jep.2015.69095