Semantic Interrelation in Distributed System Through Green Computing Ontology Herlina Jayadianti, Lukito Edi Nugroho, Paulus Insap Santosa Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta, Indonesia herlinajayadianti@gmail.com, Lukito@ugm.ac.id, insap@jteti.gadjahmada.edu Carlos Alberta Baptista Sousa Pinto Department of Information System Universidade do Minho Guimaraes Portugal csp@dsi.uminho.pt Wahyu Widayat Department Economic Development Universitas Gadjah Mada Yogyakarta, Indonesia wahyu@mep.ugm.ac.id Abstract—Green computing refers to the system that provides minimal impact on the environment. When we are talking about green computing we discuss about how much energy is used by the system, such as energy used by the system, time used for the search process, and how effective the system is. Related to that issue, trough this paper we want to proposes a new effort to achieve Green Computing in heterogeneous data in distributed system. The technology chosen to deal with them is Ontology. We try to generate a common ontology including a common set of terms, based on the several ontologies available, in order to make possible to share the common terminology (set of terms) that it implements, between different communities. If a very large amount of distributed data is not managed and distributed properly, user will need more time to do a search process. The longer the search is done, the more energy is used. Keywords—Ontology; Green Computing, Data Heterogeneity; Effectiveness; I. INTRODUCTION Support of computer systems have become part of the national infrastructure of each country. Almost the entire national infrastructure has been utilizing computers to support and offer essential and critical services either distributed or not distributed. Problem then appeared if the required data are scattered and are in a place that is different, then of course search process would become longer and takes a significant level of electrical power, thus contributing to increased fuel consumption be. The idea of the green computing has become popular in recent concern, especially if it is linked to the issue of energy crisis. Green computing focuses on how much energy the system is used and how they can make it more efficient. Related to that issue, through this paper we would like to propose a new effort to achieve an efficient search process for distributed heterogeneous data [2]. A distributed system [5] is a collection of autonomous computers linked by a computer network that appear to the users of the system as a single computer. Design issues that arise specifically from the distributed nature of the application are: (1) Transparency, (2) Heterogeneity, (3) Performance, (4) Security, and (5) Openness. In this paper we will focus only in heterogeneity problem, such as: Technical heterogeneity, data model heterogeneity and semantic heterogeneity. Semantic heterogeneity is a general term referring to disagreement about the meaning, interpretation or intended use of the same or related data. This problem is poorly a clear definition of the problem [4], [6], [7]. The importance of being aware of semantic heterogeneity and doing semantic reconciliation is to guarantee meaningful data sharing. The technology chosen to deal with semantic heterogeneity problem is Ontology. Ontologies [8], [9], [10], [11] is a model for determining semantic concepts used by various heterogeneous sources in a way that clearly defined. As more ontologies are built in a different domain, ontology heterogeneity is become another significant problem for the integration of information. Through this paper we want to prove that through ontology, can make the distribution of the data becomes easier without reducing the semantic meaning. We also want to propose a better solution in searching process to support an energy efficient [3], [18]. The objectives of this paper are to make an easy sharing semantic meaning; and to make the system can understand the tag given by each user. We will show the result trough a small implementation project. This paper is organized as follows: (1) Introduction; (2) Ontology and Green Computation; (3) Interrelation of Semantic Heterogeneity; (4) Implementation; (5) Discussion; (6) Conclusions of work. II. ONTOLOGY AND GREEN COMPUTATION Knowledge [1], [15] is people’s individual map of the world. Knowledge acquisition involves complex cognitive processes such as perception, communication, and reasoning. According to the knowledge differences, then it is possible for people have a different perception to attain awareness or understand