Organizing for Higher Performance: Case Studies of Organized Delivery Systems

Offers lessons learned from healthcare delivery systems promoting the attributes of an ideal model as defined by the Fund: information continuity, care coordination and transitions, system accountability, teamwork, continuous innovation, and easy access

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

A Model-Driven Engineering Approach for ROS using Ontological Semantics

This paper presents a novel ontology-driven software engineering approach for the development of industrial robotics control software. It introduces the ReApp architecture that synthesizes model-driven engineering with semantic technologies to facilitate the development and reuse of ROS-based components and applications. In ReApp, we show how different ontological classification systems for hardware, software, and capabilities help developers in discovering suitable software components for their tasks and in applying them correctly. The proposed model-driven tooling enables developers to work at higher abstraction levels and fosters automatic code generation. It is underpinned by ontologies to minimize discontinuities in the development workflow, with an integrated development environment presenting a seamless interface to the user. First results show the viability and synergy of the selected approach when searching for or developing software with reuse in mind.Comment: Presented at DSLRob 2015 (arXiv:1601.00877), Stefan Zander, Georg Heppner, Georg Neugschwandtner, Ramez Awad, Marc Essinger and Nadia Ahmed: A Model-Driven Engineering Approach for ROS using Ontological Semantic

A Health-care Application of Goal-driven Software Design

In this paper we focus on goal engineering by addressing issues such as goal elicitation, specification, structuring and operationalisation. Specification of business goals is regarded as a means to raise the level of abstraction (and automation) at which business logic is incorporated in model driven software design in the context of service oriented architectures. More specifically, the proposed goal modelling approach consists of an abstract syntax (metamodel) and a concrete syntax (graphical notation) for the specification of business goals. We also proposed a framework for the goal-driven design of service-oriented software applications. In particular, we illustrate our approach by means of a case study carried out in the healthcare sector and we explain the role business goals (operationalised in the form of business rules) can play in software design. This research also outlines a number of areas that have significant research potential

Situating the Next Generation of Impact Measurement and Evaluation for Impact Investing

In taking stock of the landscape, this paper promotes a convergence of methods, building from both the impact investment and evaluation fields.The commitment of impact investors to strengthen the process of generating evidence for their social returns alongside the evidence for financial returns is a veritable game changer. But social change is a complex business and good intentions do not necessarily translate into verifiable impact.As the public sector, bilaterals, and multilaterals increasingly partner with impact investors in achieving collective impact goals, the need for strong evidence about impact becomes even more compelling. The time has come to develop new mindsets and approaches that can be widely shared and employed in ways that will advance the frontier for impact measurement and evaluation of impact investing. Each of the menu options presented in this paper can contribute to building evidence about impact. The next generation of measurement will be stronger if the full range of options comes into play and the more evaluative approaches become commonplace as means for developing evidence and testing assumptions about the processes of change from a stakeholder perspective– with a view toward context and systems.Creating and sharing evidence about impact is a key lever for contributing to greater impact, demonstrating additionality, and for building confidence among potential investors, partners and observers in this emergent industry on its path to maturation. Further, the range of measurement options offers opportunities to choose appropriate approaches that will allow data to contribute to impact management– to improve on the business model of ventures and to improve services and systems that improve conditions for people and households living in poverty.

Industrialising Software Development in Systems Integration

Compared to other disciplines, software engineering as of today is still dependent on craftsmanship of highly-skilled workers. However, with constantly increasing complexity and efforts, existing software engineering approaches appear more and more inefficient. A paradigm shift towards industrial production methods seems inevitable. Recent advances in academia and practice have lead to the availability of industrial key principles in software development as well. Specialization is represented in software product lines, standardization and systematic reuse are available with component-based development, and automation has become accessible through model-driven engineering. While each of the above is well researched in theory, only few cases of successful implementation in the industry are known. This becomes even more evident in specialized areas of software engineering such as systems integration. Today’s IT systems need to quickly adapt to new business requirements due to mergers and acquisitions and cooperations between enterprises. This certainly leads to integration efforts, i.e. joining different subsystems into a cohesive whole in order to provide new functionality. In such an environment. the application of industrial methods for software development seems even more important. Unfortunately, software development in this field is a highly complex and heterogeneous undertaking, as IT environments differ from customer to customer. In such settings, existing industrialization concepts would never break even due to one-time projects and thus insufficient economies of scale and scope. This present thesis, therefore, describes a novel approach for a more efficient implementation of prior key principles while considering the characteristics of software development for systems integration. After identifying the characteristics of the field and their affects on currently-known industrialization concepts, an organizational model for industrialized systems integration has thus been developed. It takes software product lines and adapts them in a way feasible for a systems integrator active in several business domains. The result is a three-tiered model consolidating recurring activities and reducing the efforts for individual product lines. For the implementation of component-based development, the present thesis assesses current component approaches and applies an integration metamodel to the most suitable one. This ensures a common understanding of systems integration across different product lines and thus alleviates component reuse, even across product line boundaries. The approach is furthermore aligned with the organizational model to depict in which way component-based development may be applied in industrialized systems integration. Automating software development in systems integration with model-driven engineering was found to be insufficient in its current state. The reason herefore lies in insufficient tool chains and a lack of modelling standards. As an alternative, an XML-based configuration of products within a software product line has been developed. It models a product line and its products with the help of a domain-specific language and utilizes stylesheet transformations to generate compliable artefacts. The approach has been tested for its feasibility within an exemplarily implementation following a real-world scenario. As not all aspects of industrialized systems integration could be simulated in a laboratory environment, the concept was furthermore validated during several expert interviews with industry representatives. Here, it was also possible to assess cultural and economic aspects. The thesis concludes with a detailed summary of the contributions to the field and suggests further areas of research in the context of industrialized systems integration

Integrating building and urban semantics to empower smart water solutions

Current urban water research involves intelligent sensing, systems integration, proactive users and data-driven management through advanced analytics. The convergence of building information modeling with the smart water field provides an opportunity to transcend existing operational barriers. Such research would pave the way for demand-side management, active consumers, and demand-optimized networks, through interoperability and a system of systems approach. This paper presents a semantic knowledge management service and domain ontology which support a novel cloud-edge solution, by unifying domestic socio-technical water systems with clean and waste networks at an urban scale, to deliver value-added services for consumers and network operators. The web service integrates state of the art sensing, data analytics and middleware components. We propose an ontology for the domain which describes smart homes, smart metering, telemetry, and geographic information systems, alongside social concepts. This integrates previously isolated systems as well as supply and demand-side interventions, to improve system performance. A use case of demand-optimized management is introduced, and smart home application interoperability is demonstrated, before the performance of the semantic web service is presented and compared to alternatives. Our findings suggest that semantic web technologies and IoT can merge to bring together large data models with dynamic data streams, to support powerful applications in the operational phase of built environment systems