Ayalew Kassahun

Quality assurance in model based water management - review of existing practice and outline of new approaches

Quality assurance (QA) is defined as protocols and guidelines to support the proper application of models. In the water management context we classify QA guidelines according to how much focus is put on the dialogue between the modeller and the water manager as: (Type 1) Internal technical guidelines developed and used internally by the modellers organisation; (Type 2) Public technical guidelines developed in a public consensus building process; and (Type 3) Public interactive guidelines developed as public guidelines to promote and regulate the interaction between the modeller and the water manager throughout the modelling process. State-of-the-art QA practices vary considerably between different modelling domains and countries. It is suggested that these differences can be explained by the scientific maturity of the underlying discipline and differences in modelling markets in terms of volume of jobs outsourced and level of competition. The structure and key aspects of new generic guidelines and a set of electronically based supporting tools that are under development within the HarmoniQuA project are presented. Model credibility can be enhanced by a proper modeller-manager dialogue, rigorous validation tests against independent data, uncertainty assessments, and peer reviews of a model at various stages throughout its development.

A methodology to support multidisciplinary model-based water management

Quality assurance in model based water management is needed because of some frequently perceived shortcomings, e.g. a lack of mutual understanding between modelling team members, malpractice and a tendency of modellers to oversell model capabilities. Initiatives to support quality assurance focus on single domains and often follow a textbook approach with guidelines and checklists. A modelling process involves a complex set of activities executed by a team. To manage this complex, usually multidisciplinary process, to guide users through it and enhance the reproducibility of modelling work a software product has been developed, aiming at supporting the full modelling process by offering an ontological knowledge base (KB) and a Modelling Support Tool (MoST). The KB consists of a generic part for modelling, but also parts specific for various water management domains, for different types of users and for different levels of modelling complexity. MoSTs guiding component filters relevant knowledge from the KB depending on the user profile and needs. Furthermore, MoST supports different types of users by monitoring what they actually do and by producing customized reports for diverse audiences. In this way MoST facilitates co-operation in teams, modelling project audits and re-use of experiences of previous modelling projects.

A reference architecture for Farm Software Ecosystems

Display Omitted We mould the concept Software Ecosystems to the agricultural domain.We propose a reference architecture for Farm Software Ecosystems.Our reference architecture describes an organizational and technical infrastructure.We motivate that our reference architecture can improve farm enterprise integration.Our reference architecture is used to review some existing initiatives. Smart farming is a management style that includes smart monitoring, planning and control of agricultural processes. This management style requires the use of a wide variety of software and hardware systems from multiple vendors. Adoption of smart farming is hampered because of a poor interoperability and data exchange between ICT components hindering integration. Software Ecosystems is a recent emerging concept in software engineering that addresses these integration challenges. Currently, several Software Ecosystems for farming are emerging. To guide and accelerate these developments, this paper provides a reference architecture for Farm Software Ecosystems. This reference architecture should be used to map, assess design and implement Farm Software Ecosystems. A key feature of this architecture is a particular configuration approach to connect ICT components developed by multiple vendors in a meaningful, feasible and coherent way. The reference architecture is evaluated by verification of the design with the requirements and by mapping two existing Farm Software Ecosystems using the Farm Software Ecosystem Reference Architecture. This mapping showed that the reference architecture provides insight into Farm Software Ecosystems as it can describe similarities and differences. A main conclusion is that the two existing Farm Software Ecosystems can improve configuration of different ICT components. Future research is needed to enhance configuration in Farm Software Ecosystems.

Architecture Viewpoint for Modeling Business Collaboration Concerns using Workflow Patterns

Businesses today rarely operate in isolation but must collaborate with others in a coordinated fashion. To address collaboration concerns, business analysts need to design business processes. Business process designs have a direct impact on the required software systems and the corresponding architectural design. Conversely, the architectural design imposes constraints on the business process designs. Unfortunately, business processes and software architectures are often designed separately leading to a misalignment between the two. To bridge this gap we propose the architecture collaboration viewpoint to be used by teams of business analysts and software architects when addressing business collaboration concerns. The collaboration viewpoint uses elements from business process and architecture viewpoints to provide new modeling artifacts for alignment. The design artefacts are mapping tables and workflow pattern diagrams that are used to identify misalignments and redesign the business processes. The viewpoint facilitates the communication between business analysts and architects. We illustrate the collaboration viewpoint for a food supply chain transparency system from a real industrial case study.

Configuring Supply Chain Business Processes Using the SCOR Reference Model

Supply chains consist of a network of people, activities, resources and organizational systems that coordinate to move a product or services from one point to another. A typical supply chain network contains multiple different actors that have different needs and operate under different business conditions. The complex and lengthy structure of agri-food supply chains for instance makes it difficult for analysts to identify and model the appropriate business processes. Several process reference models have been provided for describing process models, but these tend to omit explicit guidance for configuring supply chain business processes particularly in the agri-food supply chains. Hence, this paper applies and adapt the SCOR model levels to demonstrate an approach for supporting configuration of supply chain business processes dedicated for supply chains. We illustrate the approach for an industrial case of a cocoa supply chain. The approach was also applied to define and model the level 4 processes which is out of scope of the SCOR model and scarce in literature for many sectors including our illustrated case.

Adopting Workflow Patterns for Modelling the Allocation of Data in Multi-Organizational Collaborations

Currently, many organizations need to collaborate to achieve their common objectives. An important aspect hereby is the data required for making decisions at anyone organization may be distributed over the different organizations involved in the collaboration. The data objects and the activities in which they are generated or used are typically represented using business process models. Unfortunately, the existing business process modeling approaches are limited in representing the complex data allocation dimensions that occur in the context of multi-organization collaboration. In this paper we provide a systematic approach that adopts workflow data patterns to explicitly model data allocations in multi-organization collaboration. To this end we propose a design viewpoint that integrates business process models with well-known data allocation problem-solution pairs defined as workflow data patterns. We illustrate the viewpoint using a case study of a collaboration research project.

Collaboration Viewpoint for Modeling Cross-Organizational Business Concerns

Organizations very often need to collaborate to achieve their business goals. Hereby it is important that the collaboration concerns are properly identified and reflected in their businesses. In practice, the business process design and architecture design are often carried out separately. This often leads to a misalignment between the business process and architecture design, a problem which becomes more severe when multiple collaborating organizations are involved. To address this problem, it is important to provide the proper design abstractions that can be used to detect and correct misalignments. To this end, we propose the architecture collaboration viewpoint that can be used by teams of business analysts and software architects when addressing business collaboration concerns. The collaboration viewpoint uses elements from business process and architecture viewpoints to provide new modeling artifacts for alignment. The design artefacts are mapping tables and workflow pattern diagrams that are used to identify misalignments and redesign the business processes. The viewpoint facilitates the communication between business analysts and architects. We illustrate the collaboration viewpoint for a food supply chain transparency system from a real industrial case study.