The transaction pattern through automating TrAM

Transaction Agent Modelling (TrAM) has demonstrated how the early requirements of complex enterprise systems can be captured and described in a lucid yet rigorous way. Using Geerts and McCarthy’s REA (Resource-Events-Agents) model as its basis, the TrAM process manages to capture the ‘qualitative’ dimensions of business transactions and business processes. A key part of the process is automated model-checking, which CG has revealed to be beneficial in this regard. It enables models to retain the high-level business concepts yet providing a formal structure at that high-level that is lacking in Use Cases. Using a conceptual catalogue informed by transactions, we illustrate the automation of a transaction pattern from which further specialisations impart a tested specification for system implementation, which we envisage as a multi-agent system in order to reflect the dynamic world of business activity. It would furthermore be able to interoperate across business domains as they would share the generalised TM as a pattern.</p

The "Artificial Mathematician" Objection: Exploring the (Im)possibility of Automating Mathematical Understanding

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer

Supporting Semantically Enhanced Web Service Discovery for Enterprise Application Integration

The availability of sophisticated Web service discovery mechanisms is an essential prerequisite for increasing the levels of efficiency and automation in EAI. In this chapter, we present an approach for developing service registries building on the UDDI standard and offering semantically-enhanced publication and discovery capabilities in order to overcome some of the known limitations of conventional service registries. The approach aspires to promote efficiency in EAI in a number of ways, but primarily by automating the task of evaluating service integrability on the basis of the input and output messages that are defined in the Web service’s interface. The presented solution combines the use of three technology standards to meet its objectives: OWL-DL, for modelling service characteristics and performing fine-grained service matchmaking via DL reasoning, SAWSDL, for creating semantically annotated descriptions of service interfaces, and UDDI, for storing and retrieving syntactic and semantic information about services and service providers

Towards smart assessment: A metamodel proposal

International audienceAssessment initiatives in organisations are focused on the evaluation of organisational aspects aiming to obtain a critic view of their status. The assessment results are used to lead improvement programs or to serve as base for comparative purposes. Assessment approaches may comprise complex tasks demanding a large amount of time and resources. Moreover, assessment results are highly dependent on the assessment input, which may have a dynamic nature due to the constant evolution of organisations. The assessment results should be adaptable to these changes without much effort whilst being able to provide efficient and reliable results. Therefore, providing smart capabilities to the assessment process or to systems in charge of performing assessments represents a step forward in the search for more efficient appraisal processes. This work proposes a metamodel defining the elements of a Smart Assessment, which is guided by elements related to the smartness concept such as knowledge, learning, reasoning and inferring capabilities. The metamodel is further specialized considering a Business Process In-teroperability Smart Assessment scenario

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

ThreMA: Ontology-based Automated Threat Modelling for ICT Infrastructures

Threat Modelling allows defenders to identify threats to which the target system is exposed. Such a process requires a detailed infrastructure analysis to map threats to assets and to identify possible flaws. Unfortunately, the process is still mostly done manually and without the support of formally sound approaches. Moreover, Threat Modelling often involves teams with different levels of security knowledge, leading to different possible interpretation in the system under analysis representation. Threat modelling automation comes with two main challenges: (i) the need for a standard representation of models and data used in various stages of the process, establishing a formal vocabulary for all involved parties, and (ii) the requirement for a well-defined inference rule set enabling reasoning process automation for threat identification. The paper presents the ThreMA approach to automating threat modelling for ICT infrastructures, aiming at addressing the key automation issues through the use of ontologies. Specifically, a formal vocabulary for modelling an ICT infrastructure, a threat catalog and a set of inference rules needed to support the reasoning process for threat identification are provided. The proposed approach has been validated against actual significant case studies provided by different Stakeholders of the Italian Public Sector

Enterprise engineering using semantic technologies

Modern Enterprises are facing unprecedented challenges in every aspect of their businesses: from marketing research, invention of products, prototyping, production, sales to billing. Innovation is the key to enhancing enterprise performances and knowledge is the main driving force in creating innovation. The identification and effective management of valuable knowledge, however, remains an illusive topic. Knowledge management (KM) techniques, such as enterprise process modelling, have long been recognised for their value and practiced as part of normal business. There are plentiful of KM techniques. However, what is still lacking is a holistic KM approach that enables one to fully connect KM efforts with existing business knowledge and practices already in IT systems, such as organisational memories. To address this problem, we present an integrated three-dimensional KM approach that supports innovative semantics technologies. Its automated formal methods allow us to tap into modern business practices and capitalise on existing knowledge. It closes the knowledge management cycle with user feedback loops. Since we are making use of reliable existing knowledge and methods, new knowledge can be extracted with less effort comparing with another method where new information has to be created from scratch

Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management.

The effective management of knowledge as capital is considered essential to the success of engineering product/service systems. As Knowledge Management (KM) and Product Lifecycle Management (PLM) practice gain industrial adoption, the question of functional overlaps between both the approaches becomes evident. This article explores the interoperability between PLM and Knowledge-Based Engineering (KBE) as a strategy for engineering KM. The opinion of key KBE/PLM practitioners are systematically captured and analysed. A set of ranked business functionalities to be fulfiled by the KBE/PLM systems integration is elicited. The article provides insights for the researchers and the practitioners playing both the user and development roles on the future needs for knowledge systems based on PLM