научная статья по теме INFORMATION SYSTEMS AND ONTOLOGY-BASED KNOWLEDGE MANAGEMENT IN THE AGRICULTURAL SECTOR Экономика и экономические науки

Текст научной статьи на тему «INFORMATION SYSTEMS AND ONTOLOGY-BASED KNOWLEDGE MANAGEMENT IN THE AGRICULTURAL SECTOR»

Information systems and Ontology-Based Knowledge Management in the agricultural sector

Figurek Aleksandra,

PhD, Faculty of Agriculture, University of Banja Luka (Republic of Srpska, Bosna and Herzegovina; e-mail: aleksandra.figurek@agrofabl.org)

Аннотация. Достижение лучших результатов в аграрном секторе требует наличие соответствующих систем для процессов контроля и оценки в сельскохозяйственном секторе. Задачи этих систем состоят в том, чтобы определить ограничивающие факторы, затрагивающие производственные действия в сельскохозяйственном секторе, и, основываясь на полном анализе ситуации, планировать соответствующие и своевременные изменения с точки зрения производственных действий. В этой статье, также введены основы концепции системы, основанной на онтологии управления знаниями в сельскохозяйственном секторе.

Abstract. Аchieving better results in the agriculture sector requires the existence of an adequate systems for monitoring and evaluation processes in agricultural sector. The tasks of this systems are to identify the limiting factors affecting the production activities in the agricultural sector, and based on a thorough review of the situation, planning appropriate and timely changes in terms of production activities. In this article, also are introduced the basics conceptions about Ontology-driven knowledge Management System in agriculture.

Ключевые слова: сельскохозяйственный сектор, информация, система управления.

Keywords: agricltural sector, informations, ma

Introduction

Management policy in agricultural sector in European Union - Common Agricultural Policy (CAP) requires reliable information about business subjects in the agriculture sector. The objectives of the CAP as defined by the Treaty of Rome, indicating the existence of two directions regarding the design priorities of the CAP, and on that basis, the appropriate information base which should provide the necessary data for the realization of the objectives in the agricultural sector. The starting point for one of these routes are the basic principles of business: productivity, profitability and efficiency of certain production factors. The second direction aims to increase the standard of living of farmers and the growth of their incomes. For this reason, data on revenues generated on farms represent a substantial component. At the same time the realization of the aforementioned objectives is difficult to achieve, given that some of them counteracting with each other.

Developers of agricultural policy must coordinate defined goals and reach a compromise in the level of their implementation. This is necessary, among other things, due to a number of constraints in the economic system of individual countries. There are three categories of restrictions that can cause weaker effects in achieving goals related to agriculture: a) agricultural production is dependent on the production technology and the availability of inputs which directly reflects the costs, b) the total value of manufactured products located directly dependent on the demand and level growth rates of population and income, c) the formation of prices of agricultural products according to market forces, which is reflected in the pricing policy and certainly affect the business of manufacturing entities at the micro and macro levels in this sector. Due to achieve a higher level of standard of living in rural areas is a central objective of the CAP, data on income earned on agricultural holdings are an essential component of the European statistical system,

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when is the agriculture sector in the question. The need for information about the business operation of agricultural holdings became evident in the 1980. During this period, on the level of the then European Community, 34% of farmers realized an income of up to 8,000 ECU (European Currency Unit) 1. Their participation accounted for 56% of the total of cultivated land, 62% of the total livestock numbers, 57% of operating capital and 63% of the total debt. Share in total employment of the workforce and contributing to the achievement of net value added of the aforementioned group of producers was 71%. The eight member states of the then EC (ie, except Luxembourg and Greece), existed as a large agricultural farms - large farmers, who exercised the total value of income in the amount of more than 40000 ECU. The other extreme was expressed by 40% of farmers who have had a negative financial result. In the above mentioned estates was present higher consumption of materials, services and funds for borrowed funds in relation to their production.

The dynamism and unpredictability of business conditions requires a high level of awareness and readiness to find effective ways to adapt to new conditions in the production processes in the agricultural sector. Two key groups of data sources on the macro level are: a) administrative sources, b) statistical censuses and statistical surveys. These sources have a different role in the development of information systems in the agricultural sector. Therefore, it is necessary to analyze all potential sources and to create a database that will be a core component of an information systems in this sector. Administrative sources provide data which are based on legislation and used to determine the rights and obligations of legal and natural persons in the agricultural sector. Examples of this type of data are data derived from tax records, rules governing the subsidization of agricultural production, data on

1 Measuring farmer's incomes and business performace, Commission of the European communities, Directorate-General X - Agricultural information, Luxemburg, 1991. p. 10.

Journal of Economy and entrepreneurship, Vol. 9, Nom. 2

ownership of land, payment of direct and indirect taxes and etc. The main aim of collecting such data is to monitor the tax collection system and the adoption of appropriate economic and financial policy. The cost of collecting this data are relatively insignificant in terms of their value, which is of great importance for the flow of information through all levels relating to the agriculture sector. Since the data are collected by using administrative systems and channels, the collected data also include data from remote and inaccessible areas. However, sometimes the two data sources, although they use the same concepts can lead to different estimates. The reasons for the existence of these differences are often known (eg, time and location of data collection are not the same.)

Statistical system of each country, primarily the part that relates to the agriculture sector, has been developed for the purpose of providing information on agricultural production, its scope, prices, import volumes. Statistical censuses and surveys are commonly used to collect data on agricultural production. Statistical censuses are means of collecting data that provides adequate coverage of the population, while the corresponding research techniques developed to reduce costs and time to collect data. Agricultural censuses and surveys are also used to collect data on the use of agricultural land, labor, agricultural production, yields, prices, machinery, etc. A certain amount of data, also taken from different administrative (official) sources (data provided by individuals and companies delivered to state authorities), while part of the data are collected through a sample survey of households. Given that agricultural production is dependent on the use of both natural and financial resources, for adequate analyzing of the agricultural sector are also necessary data about the efficiency of utilization of those resources.

Agricultural holdings are key link in the structure of information systems in the agricultural sector. Data derived based on continuous recording business events are significant components that are essential for the functioning of information systems in the agricultural sector. Improving the organizational capacities of farmers and establishing the benefits of competition in the market, depends primarily on the possession of informations. Adequate and timely information are of great importance for business holdings, due to the fact that consideration of past activities related to the production process, influencing the planning of future activities, and also on the final financial result.

Timely adoption of appropriate decisions are the cornerstone of business success for farmers. For these reasons are created systems for decision support, in order to influence faster decision making, identification of negative trends and a better allocation of economic resources. The necessity for the development of information systems, especially was expressed during the 80s and 90s of the twentieth century, when because of the technical and technological development recognized the need to have information systems in all sectors. The existence of information systems, which should contribute to the quality of planning and realization of production activities on the one hand, and evaluation funds for the realization of these activities on the other hand, have a strategic importance for the agricultural sector.

Pavri and Ang, 1995; Beath and Orlikowski, 1994; Martin, 1993; Porter and Miller, 19851 emphasize the importance of strategic planning that provide information systems.

Table 1: Development of Information Systems 2

S^ istems Characteristics

1960 Decision support systems (DSS) Computers, reducing the cost of operation, distance from the users.

1970-80 Management Information Systems (MIS) Process of information dissemination, interconnected system, regulated operation of the service.

1980-90 Strategic information systems (SIS) Integrated support system available to users associated with the business strategy.

During the last twenty years, several types of information systems3 were drafted: TPS (Transaction Process Systems), OAS (Office Automation System), MIS (M

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