The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries: A Collaborative Ethnography of Documentation Work

Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) "libraries" -- curated collections of reusable code that programmers import to perform a specific task. Software documentation for these libraries is crucial in helping programmers/analysts know what libraries are available and how to use them. Yet documentation for open source software libraries is widely considered low-quality. This article is a collaboration between CSCW researchers and contributors to data analytics OSS libraries, based on ethnographic fieldwork and qualitative interviews. We examine several issues around the formats, practices, and challenges around documentation in these largely volunteer-based projects. There are many different kinds and formats of documentation that exist around such libraries, which play a variety of educational, promotional, and organizational roles. The work behind documentation is similarly multifaceted, including writing, reviewing, maintaining, and organizing documentation. Different aspects of documentation work require contributors to have different sets of skills and overcome various social and technical barriers. Finally, most of our interviewees do not report high levels of intrinsic enjoyment for doing documentation work (compared to writing code). Their motivation is affected by personal and project-specific factors, such as the perceived level of credit for doing documentation work versus more "technical" tasks like adding new features or fixing bugs. In studying documentation work for data analytics OSS libraries, we gain a new window into the changing practices of data-intensive research, as well as help practitioners better understand how to support this often invisible and infrastructural work in their projects

An Exploration of Baby Boomer Mass Retirement Effects on Information Systems Organizations

The potential knowledge loss from Baby Boomer generation employee retirements can negatively affect information systems organizations. The purpose of this hermeneutic phenomenology study was to explore the lived experiences of the leaders and managers of information systems organizations as they tried to maintain operational continuity after Baby Boomer worker retirements. The impact of this issue was the operational continuity after the Baby Boomer worker retirement. The social impact of this issue was the knowledge loss events that might result in business loss or even bankruptcy. McElroy\u27s knowledge life cycle model was the conceptual framework for this study that included knowledge production and knowledge integration processes within a feedback loop. The lived experiences of 20 knowledgeable participants who had experienced institutional knowledge loss from retired Baby Boomer generation employees were captured through purposeful sampling. Data were collected through individual interviews using either face-to-face or a web conferencing tool such as Skype and analyzed through a modified Van Kaam. Five themes were identified: business climate, delivery practices, work processes, camaraderie, and management response. Significant attributes that added to the body of knowledge were workplace navigation, alternate focus, and outsourcing management. The results of the study may enable organizations to be better able to understand and manage the Baby Boomer knowledge loss effects and subsequently create systems to help maintain their competitive edge and avoid knowledge loss that might result in business loss or even bankruptcy

Beyond the paywall

In dieser Dissertation untersuche ich die Forschungswege von sechs Wissenschaftlern, die in verschiedenen Disziplinen und Institutionen in den Vereinigten Staaten und in der Tschechischen Republik arbeiten. Um dies zu tun, verwende ich sogenannte „multi-sited“ ethnographisch-methodische Strategien (d.h. Strategien, die Anthropologen verwenden, um Kulturen an zwei oder mehr geografischen Standorten zu vergleichen), mit dem Ziel, informationsbezogene Verhaltensweisen dieser Wissenschaftler im global vernetzten akademischen Umfeld zu untersuchen, englisch abgekürzt „GNAE“, ein Begriff, der sich speziell auf die komplexe Bricolage von Netzwerkinfrastrukturen, Online-Informationsressourcen und Tools bezieht, die Wissenschaftler heutzutage nutzen, d.h. die weltweite akademische e-IS, oder akademische Infrastruktur (Edwards et al. 2013). Die zentrale Forschungsfrage (RQ1), die in dieser Dissertation beantwortet wird, ist: Gibt es, gemäß der multi-sited ethnographischen Analyse der beteiligten Wissenschaftler in dieser Studie—Personen, die Forschung in verschiedenen Disziplinen und Institutionen sowie an unterschiedlichen Standorten betreiben—Hinweise darauf, dass ein signifikanter Anteil der nicht-institutionellen/informellen informationsbezogenen Forschung über Mechanismen im GNAE, die nicht von Bibliotheken unterstützt werden, betrieben wird, sowie (RQ2): Was für Muster sind vorhanden und wie beziehen sie sich auf informationswissenschaftliche und andere sozialwissenschaftliche Theorien? Und drittens (RQ3): Haben die Resultate praxisnahe Bedeutungen für die Entwicklung von Dienstleistungen in wissenschaftlichen Bibliotheken? Ethnographische Strategien sind bisher noch nicht in der Informationswissenschaft (IS) eingesetzt worden, um Fragen dieser Art zu untersuchen. Die Ergebnisse zeigen, dass eine informelle Informationsexploration nur bei zwei Wissenschaftlern, die mit offenen Daten und Tools einer verteilten Computing-Infrastruktur arbeiten, zu finden ist.In this dissertation I examine the pathways of information exploration and discovery of six scientists working in different research disciplines affiliated with several academic institutions in the United States and in the Czech Republic. To do so, I utilize multi-sited ethnographic methodological strategies (i.e., strategies developed by anthropologists to compare cultures across two or more geographic locations) to examine the information-related behaviors of these scholars within the global networked academic environment (GNAE), a term which specifically refers to the complex bricolage of network infrastructures, online information resources, and tools scholars use to perform their research today (i.e., the worldwide academic e-IS, or academic infrastructure [Edwards et al. 2013]). The central research question (RQ1) to be answered in this dissertation: According to the multi-sited ethnographic analysis of scientists participating in this study—individuals conducting research in various disciplines at different institutions in several geographical locations—is there evidence indicating a significant allotment of non-institutional/informal information-related exploration and discovery occurring beyond official library-supported mechanisms in the GNAE?, and—part two (RQ2) of the central research question—What (if any) patterns are exhibited and how do these patterns relate to information science (IS) and other social science theories? Both RQ1 and RQ2 are exploratory. I additionally ask (RQ3): What might all this mean in the applied sense? by showing examples of services piloted during the research process in response to my observations in the field. Multi-sited ethnographic strategies have not yet been employed in IS, as of the date of publication of this thesis, to examine such questions. Results indicate informal information exploration occurring only with two scientists who use of open data and tools on a distributed computing infrastructure

Socialising Big Data: From concept to practice

The working paper is a report on an ESRC-fundedproject, Socialising Big Data, that sought to address problematic conceptions of Big Data in popular discourse such as the ‘data deluge’ and the tendency to reduce the term to definitions such as the oft-cited‘3 Vs’. Instead, building on how social scientists have conceived of things, methods and data as having social and cultural lives, the project sought to identify the normative, political and technical imperatives and choices that come to shape Big Data at various momentsin its social lives. Recognising that Big Data involves distributed practices across a range of fields, the project experimentedwith collaboratories as a method for bringing together and engaging with practitioners acrossthree different domains –genomics, national statistics and waste management. In this way it explored how relations between data are also simultaneously relations between people and that it is through such relations that a shared literacyand social framework for Big Datacan be forged

Academic librarians’ Twitter practices and the production of knowledge infrastructures in higher education

In recent years, academic librarians’ roles have increasingly encompassed practices of knowledge production, spurred in part by their role in supporting the creation and dissemination of university research outputs. Shifts in institutional trends have also seen librarians’ widespread adoption of Twitter to share information and encourage collaboration. There is little research, however, about relationships between knowledge production in HE and librarians’ Twitter practices. The few existing studies about librarians and Twitter tend to trivialise such work as promotional. This thesis investigates the mundane work and practical politics animating academic librarians’ practices of knowledge production via Twitter. Guided by a theoretical framework about knowledge infrastructures that posits that designing and maintaining infrastructure has concomitant effects on knowledge production, this multi-sited ethnography was informed by six librarians from one UK research-intensive university. Empirical data was generated from two rounds of interviews, Twitter activity diaries, Twitter Analytics data, a focus group and written follow-up questions. Research outcomes suggest that as academic librarians negotiate the promises (i.e., the perceived potential or possibilities) of Twitter, they engage in practices of knowledge production. Four main practices of librarians implicated in their knowledge production via Twitter include justifying Twitter work as efforts to contest stereotypes of librarians (Invisibility); grounding Twitter work in modern interpretations of librarian’s ‘traditional’ values (Roots); managing the multiple scales and ambiguous engagement of Twitter (Scale); and troubling institutional hierarchies to foster scholarly community, whilst spurring new vocational identities for librarians (Culturality). By building a holistic picture of librarians’ practices, the thesis contributes insights into new and devolved practices of knowledge production in HE, thus complicating depictions of university professional groups in the scholarly literature. The study furthermore suggests that drawing attention to quiet areas of work in the university helps demonstrate the fragility and contingency of practices in HE considered static or unassailable

Documenting and Assessing Learning in Informal and Media-Rich Environments

An extensive review of the literature on learning assessment in informal settings, expert discussion of key issues, and a new model for good assessment practice. Today educational activities take place not only in school but also in after-school programs, community centers, museums, and online communities and forums. The success and expansion of these out-of-school initiatives depends on our ability to document and assess what works and what doesn't in informal learning, but learning outcomes in these settings are often unpredictable. Goals are open-ended; participation is voluntary; and relationships, means, and ends are complex. This report charts the state of the art for learning assessment in informal settings, offering an extensive review of the literature, expert discussion on key topics, a suggested model for comprehensive assessment, and recommendations for good assessment practices.Drawing on analysis of the literature and expert opinion, the proposed model, the Outcomes-by-Levels Model for Documentation and Assessment, identifies at least ten types of valued outcomes, to be assessed in terms of learning at the project, group, and individual levels. The cases described in the literature under review, which range from promoting girls' identification with STEM practices to providing online resources for learning programming and networking, illustrate the usefulness of the assessment model

Requirements of API Documentation: A Case Study into Computer Vision Services

Using cloud-based computer vision services is gaining traction, where developers access AI-powered components through familiar RESTful APIs, not needing to orchestrate large training and inference infrastructures or curate/label training datasets. However, while these APIs seem familiar to use, their non-deterministic run-time behaviour and evolution is not adequately communicated to developers. Therefore, improving these services' API documentation is paramount-more extensive documentation facilitates the development process of intelligent software. In a prior study, we extracted 34 API documentation artefacts from 21 seminal works, devising a taxonomy of five key requirements to produce quality API documentation. We extend this study in two ways. Firstly, by surveying 104 developers of varying experience to understand what API documentation artefacts are of most value to practitioners. Secondly, identifying which of these highly-valued artefacts are or are not well-documented through a case study in the emerging computer vision service domain. We identify: (i) several gaps in the software engineering literature, where aspects of API documentation understanding is/is not extensively investigated; and (ii) where industry vendors (in contrast) document artefacts to better serve their end-developers. We provide a set of recommendations to enhance intelligent software documentation for both vendors and the wider research community.Comment: Early Access preprint for an upcoming issue of the IEEE Transactions on Software Engineerin

Improving Customer Value Co-creation through Customer Engagement and Requirements Engineering Practices in a Small Software Company

A small software company has startup thinking which is often short-term. This may negate requiring planning for long-term growth, and sustainability, which could have its impact on customer value. Customer engagement (CE) and requirements engineering (RE) practices are customer satisfaction and growth oriented; helping a small software company earn competitive edge, increase productivity, and grow while delivering on customer value. To address the stated problem, the research problem is stated thus: How do CE and RE practices impact customer value (CV) co-creation? An action research study was carried out to understand better CE and RE practices at the case company. For data collection triangulation of semi-structured interviews, informal conversations, participant observation, and work experience were used. Data analysis did use some grounded theory features — interpretative statements in gathering and organizing the data got. CE practices such as having dedicated customer co-creation platform, constantly learning from users, customer segmentation, and broadened view of customer were observed to have positive influence on customer value co-creation. RE practices that advance customer value included customer participation, face-to-face-communication, continuous planning, and requirements management. The level of success of these practices was influenced by differences in customer participation level, elicitation techniques scope, and selection of the techniques. Also, lack of dedicated user environment hinders user interaction and user-centered co-creation. Customer engagement strengthens RE practices through active interaction between provider and customer to positively influence CV co-creation. Such interaction could be amongst provider, customer and end-users. There are four CE practices and seven RE practices established at the case company. Understanding CE significantly, and some of its practices, coupled with RE practices that yield high- perceived value may significantly help improve customer CV co-creation. Practices like detailed documentation, use of prototype, change and requirements management, co-creation platform, and participation in the platform can be improved upon