Fazat Nur Azizah

Generic data model patterns using Fully Communication Oriented Information Modeling (FCO-IM)

In the specific area of data modeling, data model patterns have been introduced and used to help creating highquality conceptual data models. Generic data model patterns, in particular, are expected to be more useful in helping to solve more data modeling problems in comparison to domain-specific patterns. A collection of generic patterns using Fully Communication Oriented Information Modeling (FCO-IM) as the modeling approach is described in this paper. They can generally be divided into two categories: (1) Patterns that are based on the identification of an object, consist of 5 patterns; (2) Patterns that are based on the relation between two objects, consist of 6 patterns. The generic patterns are needed to be documented in full details and then to be shared in wider audience to have comments and improvements.

Data modeling patterns using fully communication oriented information modeling (FCO-IM)

Data modeling patterns is an emerging field of research in the data modeling area Its aims are to create a body of knowledge to help understand data modeling problems better and to create better data models Current data modeling patterns are generally domain-specific patterns (only applicable in a specific domain, e.g a business situation) and with an Entity Relationship Modeling (ERM) way of thinking This paper discusses data modeling patterns using the expressive power of Fully Communication Oriented Information Modeling (FCO-IM), a Dutch Fact Oriented Modeling (FOM) method We also consider more abstract data modeling patterns – the generic patterns – and describe a few basic generic data modeling patterns in brief as well as a generic pattern found in content versioning problems.

Metadata approach in modeling multi structured data collection using object oriented concepts

In designing an enterprise wide system, a system architect must consider different concerns of the stakeholders. In this paper, we propose a generic metadata approach for modeling data with multi structure representations derived from different points of view of the stakeholders. The notion of structures/organizational views of data is separated from the collection of the data itself. We introduce two layers of the generic metamodel: (1) dataset: real data handled as a collection; (2) viewpoint: a more abstract layer describing the many structures/metadata for each point of view. The idea of datasets and viewpoints are adopted from the concepts of abstract and concrete class in object oriented modeling. To validate the generic model, we provide several case studies. We expect the proposed model provides a better architectural way of thinking in modeling an enterprise.

Review of ontology matching with background knowledge

The ontology matching process with background knowledge is more suitable to match heterogeneous ontologies, since background knowledge is used as a mediator or a reference to identify relation between two concepts being matched. This method is called indirect matching and the system is called indirect matching system. This paper reviews the motivation that described the urgency of ontology matching, the various background knowledge and their strengths, also indirect matching process. At the end we provide the comparison of indirect matching system. Based on the comparison, mapping repair function were added to improve the quality of mapping. The purpose of this paper is to help in guiding new practitioners get a general idea on the ontology matching field and to determine possible research lines.

Comparisons of diagnosis in mapping repair systems

Coherent mappings become very important things in improving the quality of alignments in ontology matching process. Mapping repairs will restore the incoherent condition into the coherent one by removing undesired correspondences. The ability to remove the undesired correspondences as minimal as possible is called minimal diagnosis. The purpose of this paper is to analyze and to compare minimal diagnosis in LogMap Repair, AML Repair, and ALCOMO. The results are comparisons of repair systems and diagnosis techniques. There are two quadrants (of four quadrants) that are matched to the goal of minimal diagnosis, namely quadrant 1 and quadrant 4. The open issues in this field will be exploring the characteristic of four quadrants and comparing them with diagnosis technique.

Generic data model pattern for data warehouse

Useful decision-making information can be proceed through a subject-oriented data warehouse in which it will store an integrated, time-variant, and non volatile collected data. The key to find such data warehouse is to have a good data model that defines the structure of data kept in the data warehouse. Actually the quality of correctness and completeness of an information depends on how well the data model is constructed. One way to get a good data model is by utilizing patterns.

Information grammar for patterns (IG P ) for pattern language of data model patterns based on fully communication oriented information modeling (FCO-IM)

The use of patterns in a design process, including data modeling, is an attempt to create a better solution to a problem. We propose the use of data model patterns, organized in a pattern language, and based on Fully Communication Oriented Information Modeling (FCO-IM) as the modeling approach, as a standard to produce high quality data models. We introduce the concept of Information Grammar for Pattern (IGP) which works as a kind of template to generate FCOIMs Information Grammar (IG). IGP is also used to define the relations among patterns. Based on how they are abstracted, we also define 3 types of IGP. The IGP provides the basic idea for the pattern language of data model patterns based on the relations among patterns.

A Conceptual Data Model for Flood Based on Cellular Automata Using Moving Object Data Model

Flood is considered as the costliest natural disaster in Indonesia due to its frequent occurrences as well as the extensive damage that it causes. Several studies provide different flood prediction models based on various hydrological factors. A lot of these models use grid-to-grid approach, making them suitable to be modelled as cellular automata. This paper presents a conceptual data model for flood based on cellular automata model using spatio-temporal data model, especially the moving object data model, as the modelling approach. The conceptual data model serves as the model of data structures within an environment for flood prediction simulation. We describe two conceptual data models as the alternatives to model the data structures of flood model. We create the data model based on the study to the factors that constitute the flood models. The first conceptual data model alternative focuses on the cell/grid as the main entity type. The changes of the states of the cells are stored as moving integer. The second alternative emphasizes on flood as the main entity type. The changes of the flood area are stored as moving region. Both alternatives introduce some advantages and disadvantages and the choice rely on the purpose of the use of the data model. We present a proposal of the architecture of a flood prediction system using cellular automata as the modelling approach. As the continuation of this work, further design and implementation details must be provided.

Database analysis and design learning tool based on problem/project-based learning

The study of database analysis and design is typically a core in an informatics/computer science undergraduate/postgraduate study program. However, a survey conducted by Connolly in 2005 concluded that in Europe, companies considered the skill of database design is the most lacking skill in IT graduate recruits. To overcome the problem, Connolly and Begg in 2006 proposed the problem/project-based learning as an approach to study database design. This paper presents our work on a learning tool on the database analysis and design, focusing on the data requirement analysis and conceptual data modeling phase. The tool is designed based on the principles of problem/project-based learning by Connolly and Begg. The learning tool is developed on top of Moodle Learning Management System (LMS) by creating a new plug-in for data modeling called DBDesign. We conducted some interviews to a number of teachers and students of informatics/computer engineering study programs to obtain some opinions about the usefulness of the learning tool in improving the database analysis and design skills. All respondents agree that the tool will help students in learning database analysis and design. Nevertheless, some features are considered to be less important than others to be provided in such database learning tool; therefore, further study is required on the features.

Source code generator for automating business rule implementation

Business rules can be implemented on business processes, business behavior, people, or software in an organization. Aligned with software development, business rules are captured from requirement elicitation and analysis, then designed and implemented in the software. The changes of business environment may affect business rules. The changes of the business rules may bring impact in the software, so that the software needs to be redeveloped. In this paper, we present a source code generator to automate business rule implementation using business rule approach. We propose a Domain Specific Language (DSL) of business rule to help expressing business rules in a business-friendly language. We also develop a business rule generator to generate source codes based on a DSL script for expressing the business rules. The proposed solution has been tested in two case studies. It is shown that the generator can help the implementation of the business rules in source codes and that the generated code can be used in business applications.