Massively distributed authorship of academic papers

Wiki-like or crowdsourcing models of collaboration can provide a number of benefits to academic work. These techniques may engage expertise from different disciplines, and potentially increase productivity. This paper presents a model of massively distributed collaborative authorship of academic papers. This model, developed by a collective of thirty authors, identifies key tools and techniques that would be necessary or useful to the writing process. The process of collaboratively writing this paper was used to discover, negotiate, and document issues in massively authored scholarship. Our work provides the first extensive discussion of the experiential aspects of large-scale collaborative research.Peer ReviewedPostprint (author's final draft

Designing distributed collaborative visual analytics systems

Analysts should be able to collaboratively work on enormous amount of available information and share their findings and understandings to effectively and efficiently make sense of the situation under investigation. The general question this thesis addresses is “How can a distributed collaborative analytics system support efficient and effective distributed (in time and space) collaboration among analysts?” and we focus on answering “How can a collaborative analytics system support efficient and effective reuse of the reasoning artefacts such as arguments, causal maps, etc.?” Through deepening our understanding of the individual and collaborative sensemaking processes that analysts go through, we identified design guidelines for enhancing, facilitating collaborative processes, fostering sharing and reuse, and improving collaboration efficiency. The design guidelines informed the design of a collaborative analytics system called AnalyticStream. We validate the proposed guidelines through the evaluation of the system

Policies, practices, and potentials for computer-supported scholarly peer review

The scholarly peer-review process has been one of the cornerstones of science for centuries, but it has also been the subject of criticism for decades. The peer-review process is increasingly supported by computer systems; however, computer support for peer review has been mostly limited to facilitating traditional peer-review processes and remedying scalability issues. We took a holistic approach to understanding the peer-review process with the goal of devising computer-supported interactions, mechanisms, and processes for improving peer review. We conducted a series of studies to investigate various aspects of the peer-review process, including procedural fairness, anonymity and transparency, reviewing motivations, politeness of reviews, and opinion measurement. In the study of fairness, we learned about researchers’ attitudes and concerns about the fairness of the peer-review process. In the study of anonymity and transparency, we learned about the diversity of anonymity policies used by various publication venues. In the study of reviewing motivations, we learned the many reasons reviewers consider reviewing as part of their academic activities and what makes a review request more likely to be accepted. In the study of the use of politeness strategies, we learned about reviewers’ use of language for mitigating criticisms in a non-blind reviewing environment. In the study of opinion measurement we iteratively designed opinion measurement interfaces that can enhance elicitation of quantitative subjective opinions. Through these five studies, we expanded the understanding of challenges and opportunities for designing better peer-review processes and systems to support them, and we presented various ways through which computer support for peer review can be enhanced to address the identified challenges.Science, Faculty ofComputer Science, Department ofGraduat