Tracking and Tracing in Food Networks: The Case of the Feed Industry

This paper discusses an organisational framework for Tracking & Tracing and quality management in the agriculture and food network and thus providing increased transparency therein. The legal and market environments that especially European companies of the compound feeds sector face today is being analyzed with respect to resulting recent and present requirements. A technological solution for companies and supply chains that helps dealing with these requirements is presented with an organisational glance inside the QM-G system.Tracking & Tracing, Feed Industry, Inter-Organizational Information System QM-G, Agribusiness, Industrial Organization,

Requirements engineering for explainable systems

Information systems are ubiquitous in modern life and are powered by evermore complex algorithms that are often difficult to understand. Moreover, since systems are part of almost every aspect of human life, the quality in interaction and communication between humans and machines has become increasingly important. Hence the importance of explainability as an essential element of human-machine communication; it has also become an important quality requirement for modern information systems. However, dealing with quality requirements has never been a trivial task. To develop quality systems, software professionals have to understand how to transform abstract quality goals into real-world information system solutions. Requirements engineering provides a structured approach that aids software professionals in better comprehending, evaluating, and operationalizing quality requirements. Explainability has recently regained prominence and been acknowledged and established as a quality requirement; however, there is currently no requirements engineering recommendations specifically focused on explainable systems. To fill this gap, this thesis investigated explainability as a quality requirement and how it relates to the information systems context, with an emphasis on requirements engineering. To this end, this thesis proposes two theories that delineate the role of explainability and establish guidelines for the requirements engineering process of explainable systems. These theories are modeled and shaped through five artifacts. These theories and artifacts should help software professionals 1) to communicate and achieve a shared understanding of the concept of explainability; 2) to comprehend how explainability affects system quality and what role it plays; 3) in translating abstract quality goals into design and evaluation strategies; and 4) to shape the software development process for the development of explainable systems. The theories and artifacts were built and evaluated through literature studies, workshops, interviews, and a case study. The findings show that the knowledge made available helps practitioners understand the idea of explainability better, facilitating the creation of explainable systems. These results suggest that the proposed theories and artifacts are plausible, practical, and serve as a strong starting point for further extensions and improvements in the search for high-quality explainable systems

Including non-functional issues in Anna/Ada programs for automatic implementation selection

We present an enrichment of the Anna specification language for Ada aimed at dealing not only with functional specification of packages but also with non-functional information about them. By non-functional information we mean information about efficiency, reliability and, in general, any software attribute measuring somehow the quality of software (perhaps in a subjective manner). We divide this information into three kinds: definition of non-functional properties, statement of non-functional behaviour and statement of non-functional requirements; like Anna annotations, all of this information appears in Ada packages and package bodies and their syntax is close to Ada constructs. Non-functional information may be considered not only as valuable comments, but also as an input for an algorithm capable of selecting the “best” package body for every package definition in a program, the “best” meaning the one that fits the set of non-functional requirements of the package in the program.Peer ReviewedPostprint (author's final draft

Identification of Variables and Information Requirements for Implementation of Traceability in Egg Production

Brazil is the 3rd largest egg producer in the Americas and for production to be achieved, it must be organized to produce with quality and productivity. For all quality requirements to be met, guidance documents such as EMBRAPA and the Brazilian Poultry Union cover all stages of the production process, from the origin of the inputs to the later stages of production. In addition to these instructions, other legislation dealing with traceability is used to regulate production processes in food chains. In this context, the objective of this work is to confront the main national and international standards related to traceability to verify common requirements and that can compose a system of data collection. The work was divided into three stages and presented as a result the common requirements: sanitary management in the breeding and rearing phases, lineage, input control, poultry vaccination, poultry feeding, sanitary monitoring, egg collection information, eggs, and biosafety, product description, batch identification, date of shipment and data of the sending company and data of the company of destination, in addition to the information retrieval system

Quality of geographic information - simple concept made complex by the context

Geographic information is increasingly being shared by many users across different fields and applications. Due to the new, widely available and easy-to-use data collection instruments and information publishing facilities the reliability of data, which is tightly coupled with its quality becomes of paramount interest. The notion of data quality is being transformed ¿ in addition to addressing the a priori requirements for data production the need for reporting the fitness for use has opened a new approach. The latter is especially pertinent in the context of Spatial Data and Information Infrastructures (SDIs). Even though the term data quality seems to be trivial, its discussion is rather difficult because of the assumptions, incoherent use of terminology and the diverging points of view. The paper will enlighten aspects of data quality from point of view of users and data producers both in the context of data production and SDIs emphasising similarities and differences. A possible way of dealing with data quality in SDIs will be described using the example of INSPIREJRC.H.6-Spatial data infrastructure

Reconfiguration patterns for Goal-Oriented Monitoring Adaptation

International audienceThis paper argues that autonomic systems need to make their distributed monitoring adaptive in order to improve their “comprehensive” resulting quality; that means both the Quality of Service (QoS), and the Quality of Information (QoI). In a previous work, we proposed a methodology to design monitoring adaptation based on high level objectives related to the management of quality requirements. One of the advantages of adopting a methodological approach is that monitoring reconfiguration will be conducted through a consistent adaptation logic. However, eliciting the appropriate quality goals remains an area to be investigated. In this paper, we tackle this issue by proposing some monitoring adaptation patterns falling into reconfiguration dimensions. Those patterns aim at facilitating the adaptation design of monitoring behavior of the whole set of distributed monitoring modules part of autonomic systems. The utility of those patterns is illustrated through a case-study dealing with monitoring adaptation based on high level quality objectives

Towards an information driven software development life cycle

Although software engineering has matured greatly over the years, a large number of ICT projects continue to fail. Studies continue to identify non-technical issues such as poor communication, shifting requirements and poor executive involvement as the main causes of these failures. This paper identifies such well known causes and poses the question as to why currently available software development life cycles fall short of dealing with them. Drawing on results from a research exercise carried out by the authors, a link is made between the quality of information used throughout the development life cycle and the quality of the resultant product. Consequently, it is proposed that organisations knowingly or unknowingly maintain a knowledge context and the quality of this knowledge context has direct impact on product quality. Furthermore, it is proposed that a software development life cycle be developed in which participants do not focus explicitly on the traditional phases of software development. Rather, a conscious decision is made to focus instead on information which is being created, manipulated and utilised throughout the lifetime of a product. If a link can be established between the quality of the knowledge context and the quality of a finished product, then it is sound to argue that if one nurtures a high quality knowledge context, a high- quality product will naturally follow.peer-reviewe