scholarly journals Modularising the Complex Meta-Models in Enterprise Systems Using Conceptual Structures

Author(s):  
Simon Polovina ◽  
Hans-Jurgen Scheruhn ◽  
Mark von Rosing

The development of meta-models in Enterprise Modelling, Enterprise Engineering, and Enterprise Architecture enables an enterprise to add value and meet its obligations to its stakeholders. This value is however undermined by the complexity in the meta-models which have become difficult to visualise thus deterring the human-driven process. These experiences have driven the development of layers and levels in the modular meta-model. Conceptual Structures (CS), described as “Information Processing in Mind and Machine”, align the way computers work with how humans think. Using the Enterprise Information Meta-model Architecture (EIMA) as an exemplar, two forms of CS known as Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are brought together through the CGtoFCA algorithm, thereby mathematically evaluating the effectiveness of the layers and levels in these meta-models. The work reveals the useful contribution that this approach brings in actualising the modularising of complex meta-models in enterprise systems using conceptual structures.

Author(s):  
Cherukuri Kumar

Knowledge discovery in data using formal concept analysis and random projections In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.


2021 ◽  
Author(s):  
◽  
Richard Lindsay Fallon

This research hypothesises is Conceptual Structures using the Resource Event Agent (REA) ontology adds value when defining a Transaction Oriented Architecture (TOA) for Enterprise Systems. Enterprise Systems drive global economic growth through well-designed implementations that provide organisations with multiple benefits, including streamlined business processes, increased efficiencies, improved productivity and decreased costs. Conversely, poorly implemented Enterprise Systems can lead to poor operating results. Most Enterprise Systems still use traditional methods of storing economic data mirroring the double-entry bookkeeping system, which can cause several problems, including data loss and repetition. Enterprise Systems must capture transaction data in a format available to multiple business processes to fulfil their goals. This thesis provides an overview of the currently available frameworks for Enterprise Architecture design. It details the problems that are observed and experienced during the completion of real-world Enterprise System development projects. The basis of the Transaction Concept is then presented as the general solution, leading to a TOA for Enterprise Systems. The Transaction Pyramid describes TOA through three layers of transactions: Enterprise, Business, and Database. The Design Science Research Methodology (DSRM) is used as the primary research methodology to provide a framework to this research. Together with the secondary research method of Action Research to provide a more granular basis for DSRM Step 3 : "Design and development", which required multiple minor iterations of the cyclical process of Action Research to produce the required artefacts. The case study approach is used also as a secondary research method for empirical inquiry and investigation required for DSRM step 4: "Demonstration". A Knowledge Management System is defined to validate TOA, and artefacts are implemented for an Automated REA (AREA) based on Protégé Frames to underpin TOA as a Proof of Concept. AREA provides a fully- edged, TOA design tool for Enterprise Architecture using the REA ontology. AREA's Knowledge Repository uses Conceptual Structures through a) the ISO Common Logic standard's Conceptual Graph Interchange Format (CGIF) to store and transmit the TOA using an REA ontology, and b) Formal Concept Analysis (FCA) for validation. AREA is then demonstrated and evaluated using two industrial case studies as exemplars. These Findings support the research's hypothesis and its contribution to knowledge.


Sign in / Sign up

Export Citation Format

Share Document