25,934 research outputs found
Impact in networks and ecosystems: building case studies that make a difference
open accessThis toolkit aims to support the building up of case studies that
show the impact of project activities aiming to promote innovation
and entrepreneurship. The case studies respond to the challenge
of understanding what kinds of interventions work in the Southern
African region, where, and why. The toolkit has a specific focus on entrepreneurial ecosystems and proposes a method of mapping out the actors and their relationships over time. The aim is to understand the changes that take place in the ecosystems. These changes are seen to be indicators of impact as
increased connectivity and activity in ecosystems are key enablers of innovation. Innovations usually happen together with matching social and institutional adjustments, facilitating the translation of inventions into new or improved products and services. Similarly, the processes supporting entrepreneurship are guided by policies implemented in the common framework provided by innovation systems. Overall, policies related to systems of innovation are by nature networking policies applied throughout the socioeconomic framework of society to pool scarce resources and make
various sectors work in coordination with each other. Most participating SAIS countries already have some kinds of identifiable systems of innovation in place both on national and regional levels, but the lack of appropriate institutions, policies, financial instruments, human resources, and support systems, together with underdeveloped markets, create inefficiencies and gaps in systemic cooperation and collaboration. In other words, we do not always know what works and what does not. On another level, engaging users and intermediaries at the local level and driving the development of local innovation
ecosystems within which local culture, especially in urban settings, has evident impact on how collaboration and competition is both seen and done. In this complex environment, organisations supporting entrepreneurship and innovation often find it difficult to create or apply relevant knowledge and appropriate networking tools, approaches, and methods needed to put their processes to work for broader developmental goals. To further enable these organisations’ work, it is necessary to understand what works and why in a given environment. Enhanced local and regional cooperation promoted by SAIS Innovation Fund projects can generate new data on this little-explored area in Southern Africa. Data-driven knowledge on entrepreneurship and innovation support best practices as well as effective and efficient management of entrepreneurial ecosystems can support replication and inform policymaking, leading thus to a wider impact than just that of the immediate reported projects and initiatives
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Similarities, challenges and opportunities of wikipedia content and open source projects
Copyright @ 2012 John Wiley & Sons, Ltd.Several years of research and evidence have demonstrated that Open Source Software (OSS) portals often contain a large amount of software projects that simply do not evolve, developed by relatively small communities, struggling to attract a sustained number of contributors. These portals have started to
increasingly act as a storage for abandoned projects, and researchers and practitioners should try and point out how to take advantage of such content. Similarly, other online content portals (like Wikipedia) could be harvested for valuable content. In this paper we argue that, even with differences in the requested expertise, many projects reliant on content and contributions by users undergo a similar evolution, and follow similar patterns: when a project fails to attract contributors, it appears to be not evolving, or abandoned. Far from a negative finding, even those projects could provide valuable content that should be harvested and identified based on common characteristics: by using the attributes of “usefulness” and “modularity” we isolate valuable content in both Wikipedia pages and OSS projects
An Introduction to Software Ecosystems
This chapter defines and presents different kinds of software ecosystems. The
focus is on the development, tooling and analytics aspects of software
ecosystems, i.e., communities of software developers and the interconnected
software components (e.g., projects, libraries, packages, repositories,
plug-ins, apps) they are developing and maintaining. The technical and social
dependencies between these developers and software components form a
socio-technical dependency network, and the dynamics of this network change
over time. We classify and provide several examples of such ecosystems. The
chapter also introduces and clarifies the relevant terms needed to understand
and analyse these ecosystems, as well as the techniques and research methods
that can be used to analyse different aspects of these ecosystems.Comment: Preprint of chapter "An Introduction to Software Ecosystems" by Tom
Mens and Coen De Roover, published in the book "Software Ecosystems: Tooling
and Analytics" (eds. T. Mens, C. De Roover, A. Cleve), 2023, ISBN
978-3-031-36059-6, reproduced with permission of Springer. The final
authenticated version of the book and this chapter is available online at:
https://doi.org/10.1007/978-3-031-36060-
QuESo: A quality model for open source software ecosystems
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Open source software has witnessed an exponential growth in the last two decades and it is playing an increasingly important role in many companies and organizations leading to the formation of open source software ecosystems. In this paper we present a quality model that will allow the evaluation of those ecosystems in terms of their relevant quality characteristics such as health or activeness. To design this quality model we started by analysing the quality measures found during the execution of a systematic literature review on open source software ecosystems and, then, we classified and reorganized the set of measures in order to build a solid quality model.Peer ReviewedPostprint (author's final draft
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