1. VERA AULIA ( 813580 )

2.  Oil palm is one of the major edible oil traded in the global market.  Oil palm tree will start to produce fruits within three years after planting and has 25 years life span with fruit production around 13 fruit bunches every year.  The oil palm plantation is rich repository of biodiversity which can be found various flora and fauna in the oil palm environment.

3.  There are more than hundred common insects and mammalian pests which intrusion and damage oil palms, such as bagworm  Most plantation owners did not realize the disease struck because of slight management can incurred huge loses of production  Oil palm disease increase every year in new type of worm, weeds and pests, it will make the data being larger and complex

4. What is data integration? Where it has been applied? Why use data integration? Problem in data integration

5.  Data integration can be defined as combination of data from different sources and be presented to the users in unified form. (Calvanese & Giacomo, 2005)

6.  Websites, education, social networks, healthcare, location-based services, communication and astronomy. (Dong & Srivastava, 2013; Zhang, 2013)

7.  Provides convenience to the users that need fast, current and clean data. (Louie et al., 2007)

8. Inconsistencies data often find in larger datasets that can affect the knowledge content, data items, information, and meta-knowledge (Zhang, 2013).  Temporal inconsistencies ◦ when time interval of two inconsistent event in temporal attributes datasets overlapping (Bleiholder & Naumann, 2011; Zhang, 2013)

9.  Text inconsistencies ◦ when two text referring to same event or entity be co-associate (Zhang, 2013)  Spatial Inconsistencies ◦ when datasets keep changing spatial distance in time (Cali et. al., 2013; Zhang, 2013)

11.  To develop a method that could integrate heterogeneous data source ◦ To identify appropriate methods to solve inconsistencies data in data integration ◦ To implement suitable methods that can be proposed in oil palm data integration ◦ To analyze and evaluate the method in development system

12. Inconsistency Data Method Solution Implementation of The Method Use In Solving Inconsistencies Data Evaluate the method in the development system

13.  Inconsistency data is one of factors that contribute to data integration problem (Jeffery et al., 2013).  Methods used: Ontology based approach (Louie et al., 2007; Nemirovski et al., 2013). Schema mapping and matching based approach (Do, 2007). Fuzzy multi-attribute decision making based approach (Wang et al., 2011). Information quality criteria approach (Angeles & Mackinno, 2011).  Ontology based approach is appropriate (Wache et al., 2001; Buccella et al., 2005).

14.  Ontology based approach Petroleum Ontology (Nimmagadda & Dreher, 2013) TBox coding (Nemirovski et al., 2013). Mappings between ontology (Wache et al., 2001) Ontology for the generation of global schemas (Hakimpour & Geppert, 2001).  Advantages of using ontology: Steady idea of the interface (Buccella et al., 2001). Language is easily communicated (Buccella et al., 2005). Increases the computational efficiency (Nemirovski et al., 2013).

15.  Nemirovski et al. (2013) TBox Intelligibility Mappings compliance Computational efficiency  Buccella et al. (2005) Architecture Semantic heterogeneity Query resolution

16.  (Luo et al., 2008) Comparing ontology model  modeling goal  model purpose  common ground within same domain  The results of evaluation can presented in appropriate accuracy for decision-making (Buccella et al.,2005)

17. Research Phase Data Collection System Model Performance Evaluation

18.  There are three phases of research methodology that need to be completed to achieve the research objectives ◦ Data collection, ◦ Framework model, ◦ Performance evaluation.

19.  Data of pests, weeds and diseases for oil palm data will collect from reference book Malaysian Palm Oil Board (MPOB)  Federal Land Consolidation and Rehabilitation Authority (FELCRA) Kedah

20.  ONv = (C, R, t) ◦ ON = ontology name, ◦ v = version number, ◦ C = {c1, …, cm} for concepts, ◦ R = {r1, …,rn} for relationships ◦ t = timestamp  OBSERVER (Ontology Based System Enhanced with Relationship for Vocabulary Heterogeneity Resolution)

21.  Ontologies and data integration ◦ ontology have three main approach which is single approach, multiple approach and hybrid approach (Wache et al.,2001)

22.  Semantic support for DSS  ontology can be used to classify different diseases by using the rule base within an expert system  Semantic query enhancement and optimization ◦ Query enhancement allows the system to provide more targeted information ◦ Query optimization is semantically altering the basic query to find a more adequate execution path within the database

23.  DESMET framework approach (Buccella et al., 2005 and Mealy & Strooper, 2006)

24.  Architecture: ◦ Information Source: OBSERVER support decision dynamic information sources and support database and HTML pages ◦ Architecture type: A wrapper imitates users’ behavior.

25.  Semantic Heterogeneity ◦ Ontology use: OBSERVER deals with inclusive relationship such as synonym, hypernym, hyponym, overlap, disjoint and covering ◦ Language : allows user to use any language (Description Logics)

26.  Query ◦ User participation: Browser performance with users query ◦ Query Plan:  First step: query construction  Access  Underlying Data  Controlled Query Expansion  Second step: Query Processor  Mapping Information  Last step: original query translated into term of user ontology ◦ Optimization: provides basic estimate information of loss measure

31. Q&A