Sustainable Software Ecosystems for Open Science

Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source professionals work together and treat software as a first-class product of scientific investigation-just as mathematics is treated in the physical sciences. Kitware has a rich history of establishing collaborative projects in the science, engineering and medical research fields, and continues to work on improving that model as new technologies and approaches become available. This approach closely follows and is enhanced by the movement towards practicing open, reproducible research in the sciences where data, source code, methodology and approach are all available so that complex experiments can be independently reproduced and verified.Comment: Workshop on Sustainable Software: Practices and Experiences, 4 pages, 3 figure

Healthy or Not: A Way to Predict Ecosystem Health in GitHub

With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development

Coopetition of software firms in Open source software ecosystems

Software firms participate in an ecosystem as a part of their innovation strategy to extend value creation beyond the firms boundary. Participation in an open and independent environment also implies the competition among firms with similar business models and targeted markets. Hence, firms need to consider potential opportunities and challenges upfront. This study explores how software firms interact with others in OSS ecosystems from a coopetition perspective. We performed a quantitative and qualitative analysis of three OSS projects. Finding shows that software firms emphasize the co-creation of common value and partly react to the potential competitiveness on OSS ecosystems. Six themes about coopetition were identified, including spanning gatekeepers, securing communication, open-core sourcing and filtering shared code. Our work contributes to software engineering research with a rich description of coopetition in OSS ecosystems. Moreover, we also come up with several implications for software firms in pursing a harmony participation in OSS ecosystems.Comment: This is the author's version of the work. Copyright owner's version can be accessed at https://link.springer.com/chapter/10.1007/978-3-319-69191-6_10, Coopetition of software firms in Open source software ecosystems, 8th ICSOB 2017, Essen, Germany (2017

Constructing Temporal Networks of OSS Programming Language Ecosystems

One of the primary factors that encourage developers to contribute to open source software (OSS) projects is the collaborative nature of OSS development. However, the collaborative structure of these communities largely remains unclear, partly due to the enormous scale of data to be gathered, processed, and analyzed. In this work, we utilize the World Of Code dataset, which contains commit activity data for millions of OSS projects, to build collaboration networks for ten popular programming language ecosystems, containing in total over 290M commits across over 18M projects. We build a collaboration graph representation for each language ecosystem, having authors and projects as nodes, which enables various forms of social network analysis on the scale of language ecosystems. Moreover, we capture the information on the ecosystems' evolution by slicing each network into 30 historical snapshots. Additionally, we calculate multiple collaboration metrics that characterize the ecosystems' states. We make the resulting dataset publicly available, including the constructed graphs and the pipeline enabling the analysis of more ecosystems.Comment: Accepted to SANER 202

ECOSENSUS: developing collaborative learning systems for stakeholding development in environmental planning

ECOSENSUS *(Electronic/Ecological Collaborative Sensemaking Support System) investigates the socio-technological issues around developing collaboration tools for participatory environmental decision making amongst (a) marginalised natural resource users, (b) professional 'experts' from different countries, and (c) key decision makers associated with managing ecosystems. An integral activity is the production of open content learning resources to support stakeholders in facilitating distributed environmental decision making. This involves the integrated use of three open source software tools: Moodle (online course management), Compendium (dialogue mapping) and uDig (user friendly desktop/internet GIS). In the first ECOSENSUS-1 phase, the pilot collaborative effort has been focused on supporting stakeholders in developing adaptive management plans for the Rupununi Wetlands in southern Guyana, a region rich in flora and fauna but also under intense pressure to expand the exploitation of its natural resources, including timber, gold, and commercially viable fish species. Results of the ECOSENSUS-1 are briefly described along with some preliminary notes on the current ECOSENUS-2 phase of associated research in Guyana supported by an additional grant from DEFRA. The paper prompts questions on how ECOSENSUS can feed into wider open source course development using the LabSpace on the OpenLearn project

Sensemaking Practices in the Everyday Work of AI/ML Software Engineering

This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and "upstream"models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities

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

Sustainable Software Ecosystems: Software Engineers, Domain Scientists, and Engineers Collaborating for Science

The development of scientific software is often a partnership between domain scientists and scientific software engineers. It is especially important to embrace these collaborations when developing advanced scientific software, where sustainability, reproducibility, and extensibility are important. In the ideal case, as discussed in this manuscript, this brings together teams composed of the world's foremost scientific experts in a given field with seasoned software developers experienced in forming highly collaborative teams working on software to further scientific research.Comment: 4 pages, submission for WSSSPE

Software\u27s Copyright Anticommons

Scholars have long assessed “anticommons” problems in creative and innovative environments. An anticommons develops when an asset has numerous rights holders, each of which has a right to prevent use of the asset, but none of which has a right to use the asset without authorization from the other rights holders. Hence, when any one of those rights holders uses its rights in ways that inhibit use of the common asset, an anticommons may result.In the software world, scholars have long argued that anticommons problems arise, if at all, because of patent rights. Copyright, on the other hand, has not been viewed as a significant source of anticommons problems. But this Article argues that copyright is an increasingly significant cause of anticommons concerns in the software context for at least two related reasons. First, the increasingly collaborative nature of much modern software innovation means that any given software resource is subject to dozens, hundreds, or even thousands of distinct copyright interests, each of which can ultimately hamper use of the software resource. While collaborative innovation licensing models help reduce the threat of any given copyright holder restricting use of the software resource, these licensing models do not altogether eliminate such risks and, in fact, actually create risks of holdup and underuse that have previously received less attention than they are due. Second, interoperability needs in the growing “Internet of Things” and “cloud” economies demand sharing and reuse of software for these ecosystems to work. Yet because these technological ecosystems implicate thousands of different parties with distinct copyright interests in their software, the threat of any one of those parties ultimately using its rights in ways that inhibit the successful development and use of the Internet of Things and cloud economies looms large. In order to illustrate some of these anticommons problems in practice, this Article examines a recent high-profile software copyright dispute between Oracle and Google.As a possible solution to these types of problems, this Article assesses the merits of more explicitly adapting copyright’s fair use defense to the collaborative and interconnected nature of modern software innovation. The Article concludes by arguing that copyright disputes in other fields of creativity characterized by collaborative, interconnected development may also merit such fair use adaptations. Otherwise, anticommons problems may increasingly affect those fields as well