642 research outputs found

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Software Supply Chain Development and Application

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    Motivation: Free Libre Open Source Software (FLOSS) has become a critical componentin numerous devices and applications. Despite its importance, it is not clear why FLOSS ecosystem works so well or if it may cease to function. Majority of existing research is focusedon studying a specific software project or a portion of an ecosystem, but FLOSS has not been investigated in its entirety. Such view is necessary because of the deep and complex technical and social dependencies that go beyond the core of an individual ecosystem and tight inter-dependencies among ecosystems within FLOSS.Aim: We, therefore, aim to discover underlying relations within and across FLOSS projects and developers in open source community, mitigate potential risks induced by the lack of such knowledge and enable systematic analysis over entire open source community through the lens of supply chain (SC).Method: We utilize concepts from an area of supply chains to model risks of FLOSS ecosystem. FLOSS, due to the distributed decision making of software developers, technical dependencies, and copying of the code, has similarities to traditional supply chain. Unlike in traditional supply chain, where data is proprietary and distributed among players, we aim to measure open-source software supply chain (OSSC) by operationalizing supply chain concept in software domain using traces reconstructed from version control data.Results: We create a very large and frequently updated collection of version control data in the entire FLOSS ecosystems named World of Code (WoC), that can completely cross-reference authors, projects, commits, blobs, dependencies, and history of the FLOSS ecosystems, and provide capabilities to efficiently correct, augment, query, and analyze that data. Various researches and applications (e.g., software technology adoption investigation) have been successfully implemented by leveraging the combination of WoC and OSSC.Implications: With a SC perspective in FLOSS development and the increased visibility and transparency in OSSC, our work provides potential opportunities for researchers to conduct wider and deeper studies on OSS over entire FLOSS community, for developers to build more robust software and for students to learn technologies more efficiently and improve programming skills

    Data science for industry 4.0 and sustainability: a survey and analysis based on open data

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    The last few years have been marked by the transition of companies and organizations to more efficient, productive and leaner practices in their processes and systems. In the spectrum of Industry and Engineering, the successful transition to Industry 4.0 is a clear goal for many Small and Medium Enterprises (SMEs) and bigger-sized companies. However, there are economic, social and environmental challenges for this transition that require innovative approaches to overcome them. The starting point for the development of this dissertation is exploring the importance of Data as a crucial resource and Data-science as a tool for companies, organizations and even public institutions to achieve innovative solutions through collaboration. As it will be further explained, Data is essential in decision making, but in many cases, organizations can’t access relevant information and tools because they are either proprietary or because there is a lack of collaboration between them and third parties. There is a common misconception that competition between companies within the same industry prohibits them from collaborating with each other. However, many times data-sharing and collaborative approaches can actually benefit both of them, increase the market they operate in, and accelerate innovation. Even though the adoption of Industry 4.0 has been already underway, this transition cannot be considered successful unless it improves sustainability across the economic, social and environmental areas of society. Those three sustainable pillars should always be considered a priority in the research of industrial and engineering evolution. Today, more than ever before, information about those topics is widely available but there is still a lack of interest by scientists and scholars in studying some of them. The following research aims to study Industry 4.0 and Sustainability themes through Data Science by incorporating open data and leveraging open-source tools in order to achieve Sustainable Industry 4.0. For that, studying the trends and current state of Industry 4.0, Sustainability and open data in the world, as well as identifying the industries, regions, and enterprises that benefit the most from Industry 4.0 adoption, and understanding if openness of data has a positive impact on Social Sustainability are the main objectives of the study. For that are used methods such as SLR (Sistematic Literature Review) in the bibliographic review and quantitative analysis through open-source software such as Python and R in the development of the research. The main results show a positive trend in Industry 4.0 adoption through sustainable practices, mainly on developed countries, and a growing trend of openness of data, which can be positive for transparency in both Industry and Sustainability.Os últimos anos têm sido marcados pela transição por parte de empresas e organizações para práticas mais eficientes, produtivas e de menores desperdícios nos seus processos e sistemas. No espectro da Indústria e Engenharia, a transição bem sucedida para a Indústria 4.0 é um objetivo claro por várias Pequenas e Médias Empresas (PMEs) e também por empresas maiores. No entanto, existem desafios de cariz económico, social e ambiental para esta transição, que requerem abordagens inovadoras para que os mesmos sejam ultrapassados. O ponto de partida para o desenvolvimento desta dissertação passou por explorar a importância de Dados como um recurso crucial e da Ciência de Dados como uma ferramenta para empresas, organizações e até mesmo instituições públicas atingirem soluções inovadoras através de colaboração. Como será explicado ao longo da dissertação, os dados são essenciais em tomadas de decisão, mas em muitos casos, as organizações não conseguem aceder a informação ou ferramentas relevantes porque ou são proprietárias, ou porque existe a falta de colaboração entre elas e terceiros. Existe também o conceito errado de que a competição entre empresas numa dada indústria as proíbe de colaborarem entre si. No entanto, muitas vezes a partilha de informação e abordagens colaborativas podem, na verdade, beneficiar ambas, expandindo o mercado onde operam e acelerando inovação. Apesar da adoção da Indústria 4.0 estar em progresso, esta transição não pode ser considerada bem sucedida se não melhorar a sustentabilidade nas áreas económicas, sociais e ambientais da sociedade. Esses três pilares da sustentabilidade devem ser considerados uma prioridade no estudo da evolução industrial e da engenharia. Hoje, mais do que nunca, a informação acerca desses tópicos é facilmente acedida, mas continua a existir interesse por parte de cientistas e académicos no estudo de alguns deles. A presente pesquisa tenciona estudar a Indústria 4.0 e temas de Sustentabilidade através de Ciência de Dados, incorporando dados abertos e explorando ferramentas open-source, para contribuir para uma Indústria 4.0 Sustentável. Para tal, estudar a tendência e estado atual da Indústria 4.0, Sustentabilidade e abertura de dados no mundo, assim como identificar as indústrias, regiões e empresas que mais beneficiam desta adoção, e finalmente compreender se uma maior abertura de dados pode ter um impacto positivo na Sustentabilidade Social são os principais objetivos do estudo. Assim, são usados métodos como RSL (Revisão Sistemática da Literatura) na revisão bibliográfica e análise quantitativa através de software open-source como o Python e R nos capítulos de desenvolvimento. Os principais resultados mostram uma tendência positiva na adoção da Indústria 4.0 através de praticas sustentáveis, principalmente em países desenvolvidos, e uma tendência crescente na abertura de dados, que pode ser positiva para uma indústria mais sustentável e transparente

    Driving and Inhibiting Factors in the Adoption of Open Source Software in Organisations

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    The aim of this research is to investigate the extent to which Open Source Software (OSS) adoption behaviour can empirically be shown to be governed by a set of self-reported (driving and inhibiting) salient beliefs of key informants in a sample of organisations. Traditional IS adoption/usage theory, methodology and practice are drawn on. These are then augmented with theoretical constructs derived from IT governance and organisational diagnostics to propose an artefact that aids the understanding of organisational OSS adoption behaviour, stimulates debate and aids operational management interventions. For this research, a combination of quantitative methods (via Fisher’s Exact Test) and complimentary qualitative method (via Content Analysis) were used using self-selection sampling techniques. In addition, a combination of data and methods were used to establish a set of mixed-methods results (or meta-inferences). From a dataset of 32 completed questionnaires in the pilot study, and 45 in the main study, a relatively parsimonious set of statistically significant driving and inhibiting factors were successfully established (ranging from 95% to 99.5% confidence levels) for a variety for organisational OSS adoption behaviours (i.e. by year, by software category and by stage of adoption). In addition, in terms of mixed-methods, combined quantitative and qualitative data yielded a number of factors limited to a relatively small number of organisational OSS adoption behaviour. The findings of this research are that a relatively small set of driving and inhibiting salient beliefs (e.g. Security, Perpetuity, Unsustainable Business Model, Second Best Perception, Colleagues in IT Dept., Ease of Implementation and Organisation is an Active User) have proven very accurate in predicting certain organisational OSS adoption behaviour (e.g. self-reported Intention to Adopt OSS in 2014) via Binomial Logistic Regression Analysis

    Understanding Sustainable Growth in Online Communities of Open-Source Software : Case: Open Core Business

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    Online communities are crucial for the survival and success of companies using the open core model, as they rely on attracting developers to use their open-source software (OSS) and con-verting some of those free users into paying customers. Current research focuses on the success factors of OSS projects, motivations to contribute, and the sustained participation from the community perspective. This thesis provides the company’s point of view and adds the concept of sustainability to the growth of online communities, which makes this topic very relevant. The main objective of thesis is to uncover the characteristics of successful communities that propitiate sustainable growth, and what are the main challenges that stand in the way by finding answers to following questions, in the context of OSS. a) What is the nature and relevance of online communities of OSS? b) What are the main factors that drive sustainable growth in online communities of OSS? c) What are the barriers for sustainable growth in online communities of OSS? To achieve this understanding, the literature review widely covers the phenomenon of open-source software communities from what they are to why are they relevant, and how can the success of these online communities be measured. Finally, the current research on sustain-able growth in online communities and its success factors and barriers are covered. To expand the current knowledge on the sustainable growth of OSS communities, a case study is con-ducted by interviewing six key members that work with the community in an open core company by using the standardized open-ended interview approach and a six-phased thematic analysis. The findings of the study identify four areas to look after when planning for sustainable growth: member’s activities, communication platforms, company involvement, and product & marketing. Among the success factors, support, engagement, and recognition are brought up as some of the key drivers. On the other hand, the data suggests the main challenges are found in the form of communication barriers, inadequate resources, brand misconceptions, social issues, and challenges in product development
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