Ontology-based patterns for the integration of business processes and enterprise application architectures

Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

Interoperability and FAIRness through a novel combination of Web technologies

Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general- or special-purpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved atthe level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs

Design Patterns for Description-Driven Systems

In data modelling, product information has most often been handled separately from process information. The integration of product and process models in a unified data model could provide the means by which information could be shared across an enterprise throughout the system lifecycle from design through to production. Recently attempts have been made to integrate these two separate views of systems through identifying common data models. This paper relates description-driven systems to multi-layer architectures and reveals where existing design patterns facilitate the integration of product and process models and where patterns are missing or where existing patterns require enrichment for this integration. It reports on the construction of a so-called description-driven system which integrates Product Data Management (PDM) and Workflow Management (WfM) data models through a common meta-model.Comment: 14 pages, 13 figures. Presented at the 3rd Enterprise Distributed Object Computing EDOC'99 conference. Mannheim, Germany. September 199

The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

Background. 
The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community.

Description. 
SADI – Semantic Automated Discovery and Integration – is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services “stack”, SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers.

Conclusions.
SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behavior we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in static triple-stores, thus facilitating the intersection of Web services and Semantic Web technologies

Responsible Composition and Optimization of Integration Processes under Correctness Preserving Guarantees

Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets - a refinement of Petri nets - we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.Comment: 37 page

A novel approach for ANFIS modelling based on Grey system theory for thermal error compensation

The fast and accurate modelling of thermal errors in machining is an important aspect for the implementation of thermal error compensation. This paper presents a novel modelling approach for thermal error compensation on CNC machine tools. The method combines the Adaptive Neuro Fuzzy Inference System (ANFIS) and Grey system theory to predict thermal errors in machining. Instead of following a traditional approach, which utilises original data patterns to construct the ANFIS model, this paper proposes to exploit Accumulation Generation Operation (AGO) to simplify the modelling procedures. AGO, a basis of the Grey system theory, is used to uncover a development tendency so that the features and laws of integration hidden in the chaotic raw data can be sufficiently revealed. AGO properties make it easier for the proposed model to design and predict. According to the simulation results, the proposed model demonstrates stronger prediction power than standard ANFIS model only with minimum number of training samples

Design patterns for smart home systems development

The information technology is increasingly entering the household and allowing the different devices integration into smart home systems. IoT (Internet of things) provides interoperability and the ability to control devices through a global network. The "smart" devices used in the environment shaping for smart home systems utilize large amounts of data that need storage, distribution and computation. There are numerous problems with the processing and security of large data sets. The design patterns can be used to solve the whole variety of emerging issues. The purpose of the report is to identify and classify the design patterns that allow different processes and devices collaboration on smart home systems

Investigating the impact of social interactions in adaptive E-Learning by learning behaviour analysis

Adaptive Educational Hypermedia Systems (AEHSs) allow for personalization of e-learning1 . Social media tools enable learners to create, publish and share their study, and facilitate interaction and collaboration2 . The integration of social media tools into AEHS offers novel opportunities for learner engagement and extended user modelling, and thereby fosters so-called Social Personalized Adaptive E-learning Environments (SPAEEs) 3. However, there has been a lack of empirical design and evaluation to elaborate methods for SPAEEs. The goal of research, therefore, is to investigate 1) the learning behaviour patterns within SPAEEs and the use of these patterns for learner engagement, 2) the evaluation methodologies for SPAEEs, and 3) the design principles for SPAEEs. Topolor4 is a SPAEE that has been under iterative development for achieving our research goals. The first prototype was used as an online learning system for MSc level students in the Department of Computer Science, at the University of Warwick, and usage data was anonymously collected for analysis5 . This poster focuses on system features and learning behaviour analysis. We firstly present the methodologies applied in the research, followed by the social and adaptive features that Topolor provides6 . Then we revisit the analysis of learning behaviours7 . Finally we propose the follow-up work based on the evaluation results