Open Source Collaboration Research Articles

Building an open-source collaborative platform for migration research: A metadata modeling approach using XML

Public access to well-organized migration data repositories is rare. While open migration data are available, most are dispersed, challenging their organization. This work uses a metadata modeling approach to organize migration-related data and research components hosted in an open-source, collaborative research environment. The proposed platform integrates data, computational models, application libraries, and research projects in a unified environment for research. An overview of the metadata modeling process and the XML technology used to integrate the platform components was provided, along with descriptions of the platform’s essential features, such as standardized exchange of information for data organization and sharing and collaborative authoring. The design of a prototype collaborative, open-source migration data and modeling research platform using sample data and software components was built and hosted on GitHub for testing and refinement purposes. It allows the authors to collaborate, improve, and assess the platform’s functionalities and capabilities. Our platform, COSMOS (Collaborative Open-Source Modeling System), adopted the creation and use of open data formats for alignment with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles to ensure that data at the prototype level is consistent with and can be used by the international migration research community in the future. By providing a standardized framework for data organization, data sharing, and collaboration, the platform can help accelerate scientific discovery and advance our understanding of complex social and cultural phenomena such as immigration.

Ara--CANINE: Character-Based Pre-Trained Language Model for Arabic Language Understanding

Recent advancements in the field of natural language processing have markedly enhanced the capability of machines to comprehend human language. However, as language models progress, they require continuous architectural enhancements and different approaches to text processing. One significant challenge stems from the rich diversity of languages, each characterized by its distinctive grammar resulting in a decreased accuracy of language models for specific languages, especially for low-resource languages. This limitation is exacerbated by the reliance of existing NLP models on rigid tokenization methods, rendering them susceptible to issues with previously unseen or infrequent words. Additionally, models based on word and subword tokenization are vulnerable to minor typographical errors, whether they occur naturally or result from adversarial misspellings. To address these challenges, this paper presents the utilization of a recently proposed free-tokenization method, such as Cannine, to enhance the comprehension of natural language. Specifically, we employ this method to develop an Arabic-free tokenization language model. In this research, we will precisely evaluate our model’s performance across a range of eight tasks using Arabic Language Understanding Evaluation (ALUE) benchmark. Furthermore, we will conduct a comparative analysis, pitting our free-tokenization model against existing Arabic language models that rely on sub-word tokenization. By making our pre-training and fine-tuning models accessible to the Arabic NLP community, we aim to facilitate the replication of our experiments and contribute to the advancement of Arabic language processing capabilities. To further support reproducibility and open-source collaboration, the complete source code and model checkpoints will be made publicly available on our Huggingface1 . In conclusion, the results of our study will demonstrate that the free-tokenization approach exhibits comparable performance to established Arabic language models that utilize sub-word tokenization techniques. Notably, in certain tasks, our model surpasses the performance of some of these existing models. This evidence underscores the efficacy of free-tokenization in processing the Arabic language, particularly in specific linguistic contexts.

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

Toward Developing High-Performance RISC-V Processors Using Agile Methodology

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Agile chip design methodology has shown promise for sustaining the scaling of computing performance more efficiently. However, practical application of this methodology has been limited by major obstacles. This article presents MinJie, an open-source platform supporting agile hardware development flow. We demonstrate the usage and effectiveness of MinJie by building two generations of XiangShan, an open-source RISC-V processor with industry-competitive performance. This article highlights the potential impact of MinJie and XiangShan in advancing the field of agile processor design and development, as well as the potential for open-source collaboration to democratize the field and drive innovation forward.</i>

LibCity-Dataset: a standardized and comprehensive dataset for urban spatial–temporal data mining

Abstract The LibCity-Dataset represents a significant contribution to the field of urban spatial-temporal data mining. This dataset uniquely integrates macro traffic state data with micro trajectory data, providing researchers with comprehensive and diverse urban spatial-temporal data. Specifically, we begin by collecting and processing existing open-source spatial-temporal data. Subsequently, we independently collected Beijing taxi trajectory data through third-party interfaces. This data bridges the gap in the scarcity of current open-source vehicle trajectory data. The distinctive aspect of the LibCity-Dataset lies in its innovative approach of standardizing the storage format, achieved through the implementation of atomic files. By adopting this standardized format, diverse data sources are harmonized, enabling effortless application of spatial-temporal prediction models across various datasets. The uniform storage format not only simplifies experimentation but also expedites the advancement of spatial-temporal prediction research, acting as a catalyst for further innovation. This Data Note provides a comprehensive insight into the creation methodology of the LibCity-Dataset, including data collection and processing methodology, data description, data validation, and usage notes. By facilitating open-source collaboration and setting a benchmark for standardization within the spatial-temporal prediction domain, this dataset aims to foster increased research cooperation and knowledge sharing. The open-source link of our dataset is https://drive.google.com/drive/folders/1g5v2Gq1tkOq8XO0HDCZ9nOTtRpB6-gPe.

Integrating Human-Centered Design and Social Science Research to Improve Service-Delivery and Empower Community Health Workers: Lessons from Project RISE

This article aims to communicate insights from a collaboration between human-centered designers and social science researchers. We report the insights from Project RISE (Rituals to Improve Service-delivery and Empower health workers), which employed a complex systems approach to understanding Accredited Social Health Activists’ motivations and performance in Bihar, India. We describe the process of interdisciplinary integration between human-centered design and mixed-method social science research. We describe insights from each phase of Project RISE. In the Discover phase, we engaged in an expansive and inclusive ideation process informing the formulation of research questions and mixed methodology. Design-led synthesis transformed research findings into actionable, context-specific insights. In the Define phase, we integrated mixed methods rigor with the design process to identify opportunities instrumental in shaping the development of design drivers and solution concepts. We engaged in inclusive prototyping and open-source collaboration to prototype productive solutions in the Create phase. We detail the challenges encountered and the strategies to address them in each phase. Integrating human-centered design and social science research can tackle community health workers’ complex challenges and create more productive public health solutions.

The Timing to Go Open: Evidence from Startups’ Open Source Innovation Activities before Acquisition

Prior studies on firms’ motivation to participate in open innovation have primarily paid attention to established firms, this study complements prior studies by investigating when startups will be motivated to go open. We propose that selecting the correct timing to go open is critical in startups’ open innovation strategy, as it shapes both the costs and benefits of going open. Leveraging IT startups’ participation in the open source collaboration platform GitHub in their pre-acquisition period as our empirical context, we show that startups first increase and then decrease their technology disclosure and collaborations on GitHub in the pre-acquisition period, and such changes are moderated by both the complexity and novelty of the technological knowledge.

Coordinating Lifesaving Product Development Projects with no Preestablished Organizational Governance Structure

We employed a longitudinal, grounded theory approach to investigate the management of an innovative product developed in the context of a life-or-death global emergency. This project involved about 40 multidisciplinary researchers, multisector companies, and open-source collaboration. Inductively, we identified the emergence and evolution of project coordination approaches, roles, and the project network along with the project's life cycle. The present study shows how configurations of these elements coevolve as the project moves forward with no predefined structures or procedures. Therefore, it provides insights for coordinating innovative projects in the face of extreme time constraints and ill-defined institutional frameworks.

Open Source Collaboration in Digital Entrepreneurship

Emerging digital technologies give rise to digital entrepreneurship and the widespread phenomenon of open source collaboration (OSC) on GitHub for entrepreneurial pursuits. Although openness is a common theme in digital entrepreneurship, it is unclear how digital startups—that is, startups that that have digital artifacts at the core of their business model for value creation and capture—actually realize value from their OSC engagement. We develop a theoretical framework to explain how the engagement in OSC may affect the value of digital startups and how the effect is contingent on the stage of venture maturity (conception, commercialization, or growth) and the mode of OSC engagement (inbound or outbound). In analyses that pool 17,552 matched digital startups with monthly panel observations between 2008 and 2017, we find digital startups in the conception and commercialization stages benefit more from inbound OSC whereas the ones in the growth stage benefit more from outbound OSC. As digital startups increasingly use OSC for ideation, experimentation, and scaling, our contribution is to show whether, when, and how knowledge flows through OSC might affect the value of digital startups. We discuss implications for research on organizing for digital entrepreneurship as well as open innovation.

“Citizens Too”: Safety Setting Collaboration Among Older Adults with Memory Concerns

Designing technologies that support the cybersecurity of older adults with memory concerns involves wrestling with an uncomfortable paradox between surveillance and independence and the close collaboration of couples. This research captures the interactions between older adult couples where one or both have memory concerns—a primary feature of cognitive decline—as they make decisions on how to safeguard their online activities using a Safety Setting probe we designed, and over the course of several informal interviews and a diary study. Throughout, couples demonstrated a collaborative mentality to which we apply a frame of citizenship in opensource collaboration, specifically (a) histories of participation , (b) lower barriers to participation, and (c) maintaining ongoing contribution. In this metaphor of collaborative enterprise, one partner (or member of the couple) may be the service provider and the other may be the participant, but at varying moments, they may switch roles while still maintaining a collaborative focus on preserving shared assets and freedom on the internet. We conclude with a discussion of what this service provider-contributor mentality means for empowerment through citizenship, and implications for vulnerable populations’ cybersecurity.

Generation of collaborative open source library services platforms: FOLIO case study

Generation of collaborative open source library services platforms: FOLIO case study

TidyMicro: a pipeline for microbiome data analysis and visualization using the tidyverse in R

BackgroundThe drive to understand how microbial communities interact with their environments has inspired innovations across many fields. The data generated from sequence-based analyses of microbial communities typically are of high dimensionality and can involve multiple data tables consisting of taxonomic or functional gene/pathway counts. Merging multiple high dimensional tables with study-related metadata can be challenging. Existing microbiome pipelines available in R have created their own data structures to manage this problem. However, these data structures may be unfamiliar to analysts new to microbiome data or R and do not allow for deviations from internal workflows. Existing analysis tools also focus primarily on community-level analyses and exploratory visualizations, as opposed to analyses of individual taxa.ResultsWe developed the R package “tidyMicro” to serve as a more complete microbiome analysis pipeline. This open source software provides all of the essential tools available in other popular packages (e.g., management of sequence count tables, standard exploratory visualizations, and diversity inference tools) supplemented with multiple options for regression modelling (e.g., negative binomial, beta binomial, and/or rank based testing) and novel visualizations to improve interpretability (e.g., Rocky Mountain plots, longitudinal ordination plots). This comprehensive pipeline for microbiome analysis also maintains data structures familiar to R users to improve analysts’ control over workflow. A complete vignette is provided to aid new users in analysis workflow.ConclusionstidyMicro provides a reliable alternative to popular microbiome analysis packages in R. We provide standard tools as well as novel extensions on standard analyses to improve interpretability results while maintaining object malleability to encourage open source collaboration. The simple examples and full workflow from the package are reproducible and applicable to external data sets.

Generation of collaborative open source library services platforms: FOLIO case study

This study aims to open source library services platforms, especially Folio platform; therefore, it seeks to identify the new generation of open source library service platforms, relying on the case study methodology to examine and analyze everything related to the emergence and development of the Folio platform, as well as studied of technical and functional characteristics. Due of importance of these new generations of automated systems, because of the acceleration of development and the short period of time between them. The study concluded that the Folio platform is still in its first start, which resulted in many things, including: the limited implementation in the world, followed by the lack of clarity of the image in case that it was applied in the Arab environment, and despite all that the platform was characterized by its many the functional and technical features and capabilities are unique form other library service platforms. This study also recommended that it is necessary to go towards participation in the Folio platform as a fertile field for investment in it by specialized companies and even professional societies and federations to contribute in development in order to have an active role in the field of developing automated systems globally as an influential field in the librarienship, especially the open source products.

Open Source Collaboration in New Ventures

Open source collaboration (OSC) platforms, such as GitHub, have emerged over the past decade to become a salient venue for organizing innovation efforts and output. As a result, an increasing number of entrepreneurial firms are collaborating with open communities on such platforms to develop and scale their new ventures. From the lens of open innovation, we examine value creation and value capture in high-tech startups’ external collaboration on OSC platforms. We develop a theoretical framework to explicate how the engagement in OSC may affect the value of startup firms and how the effect is contingent on the stage of venture maturity (conception, commercialization, or growth) and the mode of OSC engagement (inbound or outbound). In analyses that pool 22,896 matched startups with monthly panel observations between 2008 and 2017, we find a positive and significant value-added effect of OSC to startups, but the effect is sensitive to the stage of startup maturity and the mode of OSC engagement. In particular, startups in the conception and commercialization stages benefit more from inbound OSC whereas startups in the growth stage benefit more from outbound OSC. As startups increasingly rely on OSC platforms for organizing innovation, our contribution is to show whether, when, and how knowledge flows through startups’ OSC might affect the value of startup firms.

A history of the Groovy programming language

This paper describes the history of the Groovy programming language. At the time of Groovy’s inception, Java was a dominant programming language with a wealth of useful libraries. Despite this, it was perceived by some to be evolving slowing and to have shortcomings for scripting, rapid prototyping and when trying to write minimalistic code. Other languages seemed to be innovating faster than Java and, while overcoming some of Java’s shortcomings, used syntax that was less familiar to Java developers. Integration with Java libraries was also non-optimal. Groovy was created as a complementary language to Java—its dynamic counterpart. It would look and feel like Java but focus on extensibility and rapid innovation. Groovy would borrow ideas from dynamic languages like Ruby, Python and Smalltalk where needed to provide compelling JVM solutions for some of Java’s shortcomings. Groovy supported innovation through its runtime and compile-time metaprogramming capabilities. It supported simple operator overloading, had a flexible grammar and was extensible. These characteristics made it suitable for growing the language to have new commands (verbs) and properties (nouns) specific to a particular domain, a so called Domain Specific Language (DSL). While still intrinsically linked with Java, over time Groovy has evolved from a niche dynamic scripting language into a compelling mainstream language. After many years as a principally dynamically-typed language, a static nature was added to Groovy. Code could be statically type checked or when dynamic features weren’t needed, they could be turned off entirely for Java-like performance. A number of nuances to the static nature came about to support the style of coding used by Groovy developers. Many choices made by Groovy in its design, later appeared in other languages (Swift, C#, Kotlin, Ceylon, PHP, Ruby, Coffeescript, Scala, Frege, TypeScript and Java itself). This includes Groovy’s dangling closure, Groovy builders, null-safe navigation, the Elvis operator, ranges, the spaceship operator, and flow typing. For most languages, we don’t know to what extent Groovy played a part in their choices. We do know that Kotlin took inspiration from Groovy’s dangling closures, builder concept, default it parameter for closures, templates and interpolated strings, null-safe navigation and the Elvis operator. The leadership, governance and sponsorship arrangements of Groovy have evolved over time, but Groovy has always been a successful highly collaborative open source project driven more by the needs of the community than by a vision of a particular company or person.

Evolution of Do-It-Yourself Remote Monitoring Technology for Type 1 Diabetes.

The Nightscout Project is a leading example of patient-designed, do-it-yourself (DIY), open-source technology innovations to support type 1 diabetes management. We are unaware of studies that have described the evolution of patient-driven innovations from the Nightscout Project to date. We identified patient-driven, DIY innovations from posts and comments in the "CGM in the Cloud" private Facebook group as well as data from Twitter, GitHub, and the Nightscout website. For each innovation, we described its intent or its unaddressed need as well as the associated features and improvements. We conducted a thematic analysis to identify overarching patterns among the innovations, features, and improvements, and compared the timeline of innovations in the DIY space with the timing of similar innovations in the commercial space. We identified and categorized innovations in Nightscout with the most commonly appearing themes of: visualization improvements, equipment improvements, and user experience improvements. Other emerging themes included: Care Portal support, safety, remote monitoring, decision support, international support, artificial pancreas, pushover notifications, and open-source collaboration. This rapid development of patient-designed DIY innovations driven by unmet needs in the type 1 diabetes community reflects a revolutionary, bottom-up approach to medical innovation. Nightscout users accessed features earlier than if they had waited for commercial products, and they also personalized their tools and devices, empowering them to become the experts of their own care.

Developing the Chinese Academic Map Publishing Platform

The discipline of the humanities has long been inseparable from the exploration of space and time. With the rapid advancement of digitization, databases, and data science, humanities research is making greater use of quantitative spatiotemporal analysis and visualization. In response to this trend, our team developed the Chinese academic map publishing platform (AMAP) with the aim of supporting the digital humanities from a Chinese perspective. In compiling materials mined from China’s historical records, AMAP attempts to reconstruct the geographical distribution of entities including people, activities, and events, using places to connect these historical objects through time. This project marks the beginning of the development of a comprehensive database and visualization system to support humanities scholarship in China, and aims to facilitate the accumulation of spatiotemporal datasets, support multi-faceted queries, and provide integrated visualization tools. The software itself is built on Harvard’s WorldMap codebase, with enhancements which include improved support for Asian projections, support for Chinese encodings, the ability to handle long text attributes, feature level search, and mobile application support. The goal of AMAP is to make Chinese historical data more accessible, while cultivating collaborative opensource software development.

Open Source collaborations to identify new leads for Neglected Disease Drug Discovery

Open Source collaborations to identify new leads for Neglected Disease Drug Discovery

Proceedings of the EuBIC Winter School 2017

The 2017 EuBIC Winter School was held from January 10th to January 13th 2017 in Semmering, Austria. This meeting gathered international researchers in the fields of bioinformatics and proteomics to discuss current challenges in data analysis and biological interpretation. This article outlines the scientific program and exchanges that took place on this occasion and presents the current challenges of this ever-growing field. Biological significanceThe EUPA bioinformatics community (EuBIC) organized its first winter school in January 2017. This successful event illustrates the growing need of the bioinformatics community in proteomics to gather and discuss current and future challenges in the field. In addition to the organization of yearly meetings, the young and active EuBIC community aims to develop new collaborative open source projects, spread bioinformatics knowledge in Europe, and actively promote data sharing through public repositories.

A Systematic Mapping Study of Software Development With GitHub

Context: GitHub, nowadays the most popular social coding platform, has become the reference for mining Open Source repositories, a growing research trend aiming at learning from previous software projects to improve the development of new ones. In the last years, a considerable amount of research papers have been published reporting findings based on data mined from GitHub. As the community continues to deepen in its understanding of software engineering thanks to the analysis performed on this platform, we believe that it is worthwhile to reflect on how research papers have addressed the task of mining GitHub and what findings they have reported. Objective: The main objective of this paper is to identify the quantity, topic, and empirical methods of research works, targeting the analysis of how software development practices are influenced by the use of a distributed social coding platform like GitHub. Method: A systematic mapping study was conducted with four research questions and assessed 80 publications from 2009 to 2016. Results: Most works focused on the interaction around coding-related tasks and project communities. We also identified some concerns about how reliable were these results based on the fact that, overall, papers used small data sets and poor sampling techniques, employed a scarce variety of methodologies and/or were hard to replicate. Conclusions: This paper attested the high activity of research work around the field of Open Source collaboration, especially in the software domain, revealed a set of shortcomings and proposed some actions to mitigate them. We hope that this paper can also create the basis for additional studies on other collaborative activities (like book writing for instance) that are also moving to GitHub.