Investigating Ontology Development and Usage in Horticultural Production

Transcription

1 Investigating Ontology Development and Usage in Horticultural Production Michael T. Maliappis a a Agricultural University of Athens, Greece, michael@aua.gr Abstract Despite the growing number of ontologies online available, their range of application in real world projects is comparatively limited. The main purpose, in this paper, is to construct an ontology targeting horticultural domain of Agriculture and examine its usefulness in particular areas. The proposed ontology is going to be used, (a) as a refine tool facilitating searching process in bibliographic databases or digital libraries, (b) as a classification mechanism helping the process of storage and retrieval in a digital library system and (c) as a domain model for rule knowledge base construction. Apart from the ontology development, this paper presents a prototype web application which uses ontology in combination with a rule base concerning pest management in tomato cultivations in low-technology greenhouses. The described application provides access to an inference engine through web service architecture. End user is able to submit instances of his/her data in a proper XML format, and receives on his/her screen the suggestions of the underlying expert system. A second prototype web based application shows how the same ontology can be used to browse the stored material of a digital library. A guided, by domain ontology, searching process, would be able to direct the user to find more clearly and easily the desired information. Key words: ontology, knowledge sharing and reuse, horticultural ontology, ontology construction, ontology usage. 1 Introduction Knowledge collection and representation in a usable and efficient way is a cumbersome, time consuming and expensive process. Sharing of the same knowledge in different applications and its reuse without or little modifications in solving separate problems is a critical factor in knowledge dissemination. Among knowledge representation techniques ontologies formalization can be used to model real world in a consistent, formal, manageable and reusable way. Ontologies can be used to facilitate several aspects of knowledge management such as knowledge representation, knowledge sharing and reuse, knowledge classification and knowledge search and retrieval. According to Gruber (1993) ontology is an explicit specification of a conceptualization. Conceptualization is considered as an abstract view of the domain of interest. A particular ontology associates vocabulary terms with entities identified in the conceptualization of the domain and provides definitions to constrain the interpretations of these terms. In other words, ontologies present a common understanding for a particular domain and they supply a way to represent knowledge in a systematic and disciplined manner. Ontologies are an ideal communication tool among domain experts and between them, knowledge engineers and end users. Ontologies can be used to describe knowledge domains and are useful as searching aiding tools providing multilingual or synonym navigational capabilities. They can be used to support searching using terms in different languages, to navigate through a body of knowledge or to assist knowledge mining from several sources. Their structure and the concepts govern their formalization facilitates knowledge sharing and reuse. They can be used to homogenize heterogeneous sources of knowledge and provide a common level

2 of appearance. They, also, can be used to provide taxonomy of knowledge. A taxonomy is a hierarchical structure for organizing a body of knowledge; it gives a framework for understanding and classifying knowledge how to group it and how the various groups are related to each other. This last facility in addition with metadata extraction makes ontologies a useful tool in resource (documents, images, etc.) classification, indexing and retrieval in the area of digital libraries. There are several efforts towards the construction of ontologies in several fields. The existence of standard representation languages, such as RDF Schema or OWL, for ontology development, facilitates sharing and reuse and the possibility to merge various ontologies into a more representative one. In Agriculture domain, there is a number of initiatives towards the development of specific ontologies (Koenderink et al., 2005; Beck et al., 2005). Among the most interesting and promising endeavors is the work carried on in FAO (Beck and Pinto, 2002). FAO started several initiatives towards the construction of agricultural domain ontologies based on multilingual AGROVOC (FAO s Multilingual Agricultural Thesaurus) (Soergel et al., 2004) through the Agricultural Ontology Service (AOS) project (FAO, 2001). The resulted ontologies have been used for guided search and navigation into the underlying knowledge. According to Simprel and Tempich (2006), despite the growing number of ontologies online available, their range of application in real world projects is comparatively limited. The main purpose, in this paper, is to construct an ontology targeting horticultural domain of Agriculture and examine its usefulness in particular areas. The proposed ontology is going to be used, (a) as a refine tool facilitating searching process in bibliographic databases or digital libraries, (b) as a classification mechanism helping the process of storage and retrieval in a digital library system and (c) as a domain model for rule knowledge base construction. The proposed ontology describes production of horticultural crops in low technology greenhouses and includes several financially important vegetable crops in the area of Mediterranean basin (tomato, pepper and aubergines). Among the objectives of the proposed ontology is the systematic organization and representation of knowledge and terminology, concerning all the stages in horticultural production and marketing. Apart from the ontology development, this paper presents a prototype web application which uses ontology in combination with a rule base concerning pest management in tomato cultivations. The described application provides access to an inference engine through web service architecture. End user is able to submit instances of his/her data in a proper XML format, and receives on his/her screen the suggestions of the underlying expert system. A second prototype web based application shows how the same ontology can be used to browse the stored material of a digital library. A guided, by domain ontology, searching process, would be able to direct the user to find clearly and easily the desired information or knowledge and help in its proper application in the daily activities of farmers. The rest of this paper provides a background section with information on concepts, methodologies and tools, describes ontology and its development process and presents two case studies on ontology usage. 2 Background There are several ways to organize and represent knowledge depending on the knowledge domain and the ultimate usage purpose. In this particular case, knowledge structure is needed to facilitate a clearer organization of domain knowledge and, in parallel, to assist indexing and searching of information material relevant to this specific domain. The most interesting structure serving these purposes is ontology. Ontology is a formal explicit description of concepts in a domain of discourse providing a common understanding for a particular domain. Ontologies can be used to describe knowledge domains and are useful as searching aiding tools providing multilingual and synonym capabilities. Domain ontologies can be used to establish a common vocabulary as to facilitate semantic interpretation of terms, sharing and organization of knowledge. Enable reuse of domain knowledge, make domain assumptions explicit and used to analyze domain knowledge. Moreover, ontologies can be used for knowledge classification or taxonomy. The purpose of taxonomy is to organize knowledge so that users can more easily navigate their way through it. Taxonomies can be generated either manually or automatically using software programs. Until recently, knowledge classification and taxonomy had been accomplished using thesauri. A thesaurus is a list of the various terms describing a body of knowledge and a language which specifies relationships between the terms: antonyms and synonyms, broader terms and narrower terms, etc. In

3 content management, the aim of a thesaurus is to enable content to be indexed in a variety of ways so that different users who tend to use different terms can still find it. In the agricultural sector there are many well-established and authoritative controlled vocabularies, such as AGROVOC, the CAB Thesaurus, and NAL Thesaurus (the thesaurus of the National Agricultural Library in the United States). However, for these thesauri to be useable beyond their original scope there is a need to re-assess the traditional "thesaurus" approach and move towards modern technologies that are more suited to a web environment, such as ontologies. There are several initiatives towards the organization of the vocabulary concerning several aspects of the Agricultural sector. Most of them (AGROVOC, etc.) are restricted to the implementation of thesaurus having loosed coupling between the various terms. Nowadays, the intention is to convert these thesauri into more cohered structures such as ontologies. Domain ontology can be used in combination with search engines and expert systems technologies to accomplish the required tasks in an efficient way. Search engine is a piece of software that carries out searches for information across multiple sources. Search engines vary widely in their level of sophistication. Some simply allow users to search for documents that contain a specific word or phrase, which can leave users having to sift through great deal of irrelevant information. More advanced search engines allow users to construct more specific searches, enabling them to narrow their search and reduce the amount of irrelevant material retrieved. Expert systems are software applications that use domain knowledge to solve problems. Among the several kinds of expert systems, those constructed using rulebased knowledge representation appears to be better adapted to particular applications, such as diagnosis. Since knowledge collection is a difficult and expensive process, the selected knowledge representation structure should promote knowledge reuse and sharing. Knowledge reuse can be defined as the possibility to use knowledge in one or more applications in different time points, and knowledge sharing as the possibility to use knowledge from several applications at the same time (Uschold et al., 1999). Adopting a more broad definition it is possible to cover both definitions under the term of reuse. Nevertheless, the two situations can be implemented using the same techniques. According to Krueger (1992) and Freeman (1991), software reuse is the process of using already existed software artifacts (code, test cases, designs, prerequisites, documentations, domain knowledge and development processes) to construct new software systems, instead of the development of them from scratch. 3 Ontology Construction Usage of production rules in expert system applications is a predominant way in knowledge base construction. Production rules offers a rich expressive environment accompanied with a freedom in expression and design. During development of several knowledge bases and specific expert systems (Mahaman et al., 2003; Passam et al., 2001; Yialouris et al., 1997) has been recognized that formalization and standardization of the needed knowledge is an absolute necessity towards the construction of efficient and robust applications. Trying to construct expert systems based on the popular and loose IF-THEN rule reasoning structure after a while the whole process leaded into a confusion stage. Lack of a formal and disciplined way of knowledge representation made development process a difficult task. Starting from these observations an effort was started to investigate other possible knowledge representations which, keeping the same expressive power, will offer more discipline and opportunities for knowledge reuse, allowing easy reengineering of expert system applications developed so far. Ontologies were identified as the knowledge structure filling theses requirements. So an endeavour started to develop an ontology, under the name of OntoCrop, covering a portion of the horticultural domain and the cultivation of vegetable crops in low-technology greenhouses. Since ontology construction is an evolutionary process and goes through several stages until its completion, its development started from the part needed for reengineering the already existed applications. Afterwards, it is going to be extended to cover more parts of the horticultural domain. Emphasis has been set to a clear and consistent description of the domain under investigation. Furthermore, exploiting reuse capabilities of ontologies, the same ontology has been used to assist organizing and searching for information. At a second stage, ontology has been augmented with characteristics enhancing its usefulness in knowledge searching. For this purpose ontology has been

4 enriched with synonyms, and in some cases with antonyms, of the main terms in English and Greek. Multilanguage dimension is an important issue in countries with native languages different than the dominant languages and more especially than English. So, the capability for knowledge indexing and searching in native language, in parallel with English, is a crucial factor in application usefulness. OntoCrop has been constructed using Protégé 1 software. Protégé is a free, open-source platform that provides a suite of tools to construct domain models and knowledge-based applications with ontologies. It implements a rich set of knowledge-modelling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protégé provides a friendly environment for ontology construction and has also the capability to convert ontology in several structures such as RDF, OWL or XML. Additionally, it offers a Java API to programmatically access the stored knowledge. Among the knowledge contained in OntoCrop are cultivation techniques, pest management, crops physiology and commerce. Ontology has, also, been extended to include knowledge concerning propagation, cultivation techniques, post-harvest physiology, consumption and marketing. Using the proposed ontology, users can extract useful knowledge on vegetable species cultivated in low technology greenhouses in the Mediterranean Basin and especially in Greece, such as tomato, aubergine, bean, cucumber, lettuce, and pepper. 4 Case Studies For the purpose to check the usefulness and suitability of the constructed ontology, two prototype web applications has been developed. The first one is used to investigate usefulness of the ontology in expert system development using IF-THEN rule reasoning structure and the second to check the same ontology in facilitating indexing and searching process in DSpace repositories. Both web applications have been developed using open source software and subsystems based on J2EE (Java 2 Enterprise Edition) platform, a standard for implementing and deploying scalable, reliable and secure distributed applications. Among the open-source technologies can be identified the Eclipse development environment, Struts and Spring frameworks and Hibernate object-relation mapping tool. Applications use a 3-tier architecture comprised of a presentation tier, web and service tier, and data tier. This architecture can be deployed using a single application server. The application server encapsulates the service tier, which consists of the business and data logic. Web and service tier communicates with the data tier through the JDBC (Java Data Base Connectivity) protocol. The client tier is a very thin tier that contains only presentation logic. The implementation allows the ordinary user to access the system through a simple web browser. According to this architecture, specialized equipment (hardware and software) is needed only on the server site. 4.1 Using Ontology in Rule Reasoning The first application aims in reengineering a previous developed application (Passam et al., 2001) which uses IF-THEN rules to incorporate OntoCrop in the construction of rules. The initial system was a diagnostic expert system which could be used to identify the principal pests, diseases and nutritional disorders of six common vegetable crops (aubergine, bean, cucumber, lettuce, pepper and tomato) and provide guidance for their control. The system covered the pests and nutritional disorders most frequently encountered during cultivation of the abovementioned crops under plastic covered greenhouses in the Mediterranean region. Knowledge of the rule system had been derived from practical experience and literature sources. The system accepted as input the visual symptoms of the disorder and advised for the source of the problem indicating possible ways of treatment. Since the initial expert system was constructed using IF-THEN rules, its development wasn t based on a disciplined methodology. No preliminary work was necessary to start knowledge base construction. The 1

5 freedom, provided in construction of rules, easily leads, sometimes, to confusion in separation of concepts, as the knowledge base is being expanded with new rules. A common mistake is the identification of the same concept in separate rules with slightly different wording. On the other site, it is very difficult to identify any relationships between concepts or mere the set of the used concepts. Rules contain a rich amount of knowledge which is not easily useable in any other way apart of the initial purpose of the building of the expert system. Reengineering of the expert system started from the construction of OntoCrop describing the set of concepts contained in the rules. During the process were identified duplications in concepts and relationships between them. The rules were rewritten using the refined concepts of the ontology. The web application, implemented to exploit ontology in rule reasoning, uses web services technology in its construction. Web services implemented in Java and deployed using Apache AXIS. Access to ontology contents had been accomplished using Protégé API. Application s front end accepts input data through special forms, converts them in XML format and forwards them to the server. The reverse process is followed to present the results to the user. 4.2 Using Ontology in Indexing and Searching The second application uses ontology to assist indexing and searching of information material (documents, images, etc) relevant to crop cultivation domain. Information material is stored in a DSpace 2 repository which uses Apache Lucene 3 as search engine. An interesting characteristic of the application is its ability to search for terms in several languages having as input the term in one of the language. This can be accomplished with the assistance of the term synonyms contained in the ontology. DSpace is an open source software platform that enables organizations to capture, describe and preserve digital assets and provides distributed access to these assets through a search and retrieval subsystem. Lucene is an open source search engine and is used by DSpace to implement indexing and searching facilities. Lucene provides stop word removal, stemming, and the ability to incrementally add new indexed content without regenerating the entire index. The two software products are highly extendable. Lucene has been modified to incorporate customized indexing and searching processes. Ontology should be used first for indexing of the material (documents, images, maps, etc) contained in the DSpace repository. Afterwards, using a properly designed user interface, the application allows searching or browsing the stored material using OntoCrop concepts, terms and their relationships. Navigation guided by ontology has been assisted by AJAX technology. AJAX allows the asynchronous receive of the results of the search requests without the disturbance of the other portions of the displayed content. 5 Conclusion This paper describes the initial endeavours for the development of an ontology concerning the horticultural domain. Through its use, in the previously described web applications, the proposed ontology passed several rounds of refinement. At its current stage of development it contains useful knowledge targeted to several kinds of users. Students can consult the ontology to identify and learn concepts and relationships between them for the horticultural domain. Growers are able to search for useful knowledge concerning specific cultivation techniques in the field. Moreover, consumers are able to consult the ontology to identify several characteristics of crops, such as appearance, touch, smell, ingredients which concern their use as food. A guided searching process with the help of domain representation structures, such as domain ontologies, would be able to direct the user to find more clearly and easily the desired information or knowledge and

6 help in proper application of knowledge in the daily activities of farms. Quality, precision and accuracy of the searching results are heavily depended on the quality of domain ontology and indexing process. At this time, ontology has been used only for the development of the two web applications. This is an initial evaluation process which should be extended by introducing its usage in education procedures and opens its access to the public. In the future, the proposed ontology is going to be augmented to include more portions of the horticultural domain. Furthermore, an application is going to be developed offering access, searching and navigation, to OntoCrop ontology using web services technology. Acknowledgements This work is supported by the PYTHAGORAS-II research project, which is co-funded by the European Social Fund and Greek national resources (EPEAEK II). 6 References Beck, H., and H. S. Pinto Overview of Approach, Methodologies, Standards, and Tools for Ontologies., Agricultural Ontology Service, UN FAO. Beck, H.., Soonho K., and D. Hagan A Crop-Pest Ontology for Extension Publications. Proceedings of 2005 EFITA/WCCA Joint Congress on IT in Agriculture Vila Real, Portugal. FAO Agricultural Ontology Service (AOS)"A tool for Facilitating Access to Knowledge" - Concept Note Version 5.5. Rome, Italy. Freeman, P Reusability: Progress or Repetition? Keynote address at the First International Workshop on Software Reusability, Dortmund, Germany. Gruber, T. R A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5, no. 2: Koenderink, Nicole J. J. P., Jan L. Top, and Lucas J. van Vliet Expert-Based Ontology Construction: a Case-Study in Horticulture. 16th International Workshop on Database and Expert Systems Applications (DEXA'05). Krueger, C. W Software Reuse. ACM Computing Surveys 24, no. 2. Mahaman, B. D., H. C. Passam, A. B. Sideridis, and C. P. Yialouris DIARES-IPM: a diagnostic advisory rule-based expert system for integrated pest management in Solanaceous crop systems. Agricultural Systems 76: Passam, H. C., A. B. Sideridis, C. P. Yialouris, and M. T. Maliappis Improvement of Vegetable Quality and Water and Fertilizer Utilization in Low-Tech Greenhouses Through a Decision Support Management System. Journal of Vegetable Crop Production 7, no. 1: Simperl E. P. B., and C. Tempich Ontology Engineering: a Reality Check. 5th International Conference on Ontologies, Databases, and Applications of Semantics (ODBASE2006). Soergel, D., B. Lauser, A. Liang, F. Fisseha, J. Keizer, and S. Katz Reengineering Thesauri for New Applications: the AGROVOC Example. Journal of Digital Information 4, no. 4. Uschold, M., R. Jasper, and P. Clark Three Approaches for Knowledge Sharing: A Comparative Analysis. In Proc 12th Workshop on Knowledge Acquisition, Modelling and Management (KAW'99). Yialouris, C. P., H. C. Passam, A. B. Sideridis, and C. Metin VEGES: A multilingual expert system for diagnosis of pests, diseases and nutritional disorders of six greenhouse vegetables. Computers and Electronics in Agriculture 19: