6,407 research outputs found

    Hack Weeks as a model for Data Science Education and Collaboration

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    Across almost all scientific disciplines, the instruments that record our experimental data and the methods required for storage and data analysis are rapidly increasing in complexity. This gives rise to the need for scientific communities to adapt on shorter time scales than traditional university curricula allow for, and therefore requires new modes of knowledge transfer. The universal applicability of data science tools to a broad range of problems has generated new opportunities to foster exchange of ideas and computational workflows across disciplines. In recent years, hack weeks have emerged as an effective tool for fostering these exchanges by providing training in modern data analysis workflows. While there are variations in hack week implementation, all events consist of a common core of three components: tutorials in state-of-the-art methodology, peer-learning and project work in a collaborative environment. In this paper, we present the concept of a hack week in the larger context of scientific meetings and point out similarities and differences to traditional conferences. We motivate the need for such an event and present in detail its strengths and challenges. We find that hack weeks are successful at cultivating collaboration and the exchange of knowledge. Participants self-report that these events help them both in their day-to-day research as well as their careers. Based on our results, we conclude that hack weeks present an effective, easy-to-implement, fairly low-cost tool to positively impact data analysis literacy in academic disciplines, foster collaboration and cultivate best practices.Comment: 15 pages, 2 figures, submitted to PNAS, all relevant code available at https://github.com/uwescience/HackWeek-Writeu

    Taking statistical machine translation to the student translator

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    Despite the growth of statistical machine translation (SMT) research and development in recent years, it remains somewhat out of reach for the translation community where programming expertise and knowledge of statistics tend not to be commonplace. While the concept of SMT is relatively straightforward, its implementation in functioning systems remains difficult for most, regardless of expertise. More recently, however, developments such as SmartMATE have emerged which aim to assist users in creating their own customized SMT systems and thus reduce the learning curve associated with SMT. In addition to commercial uses, translator training stands to benefit from such increased levels of inclusion and access to state-of-the-art approaches to MT. In this paper we draw on experience in developing and evaluating a new syllabus in SMT for a cohort of post-graduate student translators: we identify several issues encountered in the introduction of student translators to SMT, and report on data derived from repeated measures questionnaires that aim to capture data on students’ self-efficacy in the use of SMT. Overall, results show that participants report significant increases in their levels of confidence and knowledge of MT in general, and of SMT in particular. Additional benefits – such as increased technical competence and confidence – and future refinements are also discussed

    IDMB archaeology case study: Summary

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    Providing guidance on Backstage, a novel digital backchannel for large class teaching

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    Many articles in the last couple of years argued that it is necessary to promote the active participation of students in lectures with large audiences. One approach to make students actively participate in a lecture is to use a digital backchannel, i.e. a computer-mediated communication platform that allows students to exchange ideas and opinions, without disrupting the lecturer’s discourse. Though, a digital backchannel, in order to be most helpful for learning, have to address the need for guidance of the users interacting. The article presents Backstage, a digital backchannel for large class lectures, and shows how it provides guidance for its users, i.e. the students but also the lecturer. Structural guidance is provided by aligning the usually incoherent backchannel discourse with the presentation slides that are integrated in the backchannel’s user interface. The alignment is thereby asserted by carefully designed backchannel workflows. The article also discusses the guidance of a student’s substantial involvement in both the frontchannel and the backchannel by means of scripts. Through the interactions of guided individuals a social guidance may emerge, leading to a collectively regulated backchannel

    Serverification of Molecular Modeling Applications: the Rosetta Online Server that Includes Everyone (ROSIE)

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    The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org
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