6,407 research outputs found
Hack Weeks as a model for Data Science Education and Collaboration
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
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 studentsâ 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 â such as increased technical competence and confidence â and future refinements are also discussed
Providing guidance on Backstage, a novel digital backchannel for large class teaching
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 lecturerâs 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 backchannelâs user interface. The alignment is thereby asserted by carefully designed backchannel workflows. The article also discusses the guidance of a studentâs 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)
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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