The real argument, then, is not about when and how traditional formats like the PDF will be replaced; it’s about accepting that the familiar (and perhaps boring) research article still has its purpose, while at the same time thinking ambitiously and creatively about how the humble document can be supplemented with the modern features and functions that the digital environment offers.
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fatcat! - 1 views
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"Fatcat is a versioned, user-editable catalog of research publications: journal articles, conference proceedings, pre-prints, etc. Features include archival file-level metadata (verified digests and long-term copies, in addition to URLs), a documented API, and work/release indexing (aka, linking together of pre-prints and final copies)."
Ways to Compute Topics over Time, Part 1 · from data to scholarship - 0 views
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"This the first in a series of posts which constitute a "lit review" of sorts to document the range of methods scholars are using to compute the distribution of topics over time."
Study documents economic gains from liberal arts education - 0 views
Topic Modeling in Python with NLTK and Gensim | DataScience+ - 0 views
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"In this post, we will learn how to identify which topic is discussed in a document, called topic modeling. In particular, we will cover Latent Dirichlet Allocation (LDA): a widely used topic modelling technique. And we will apply LDA to convert set of research papers to a set of topics."
Digital History & Argument White Paper - Roy Rosenzweig Center for History and New Media - 0 views
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"This white paper is the product of the Arguing with Digital History Workshop organized by Stephen Robertson and Lincoln Mullen of George Mason University, with funding from the Andrew W. Mellon Foundation. The two-day workshop, which involved twenty-four invited participants at different stages in their careers, working in a variety of fields with a range of digital methods, was conceived with a focus on one particular form of digital history, arguments directed at scholarly audiences and disciplinary conversations. Despite recurrent calls for digital history in this form from digital and analog historians, few examples exist. The original aim of the workshop was to promote digital history that directly engaged with historiographical arguments by producing a white paper that addressed the conceptual and structural issues involved in such scholarship. Input from the participants expanded the scope of the white paper to also elaborate the arguments made by other forms of digital history and address the obstacles to professional recognition of those interpretations. The result was a document that aims to help bridge the argumentative practices of digital history and the broader historical profession. On the one hand, it aims to demonstrate to the wider historical discipline how digital history is already making arguments in different forms than analog scholarship. On the other hand, it aims to help digital historians weave the scholarship they produce into historiographical conversations in the discipline."
Guest Post: Is the Research Article Immune to Innovation? - The Scholarly Kitchen - 0 views
The "Digital" Scholarship Disconnect | EDUCAUSE - 0 views
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Digital scholarship is an incredibly awkward term that people have come up with to describe a complex group of developments. The phrase is really, at some basic level, nonsensical. After all, scholarship is scholarship. Doing science is doing science. We don't find the Department of Digital Physics arguing with the Department of Non–Digital Physics about who's doing "real" physics.
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Soon, people wanted to start talking more broadly about newly technology-enabled scholarly work, not just in science; in part this was because of some very dramatic and high-visibility developments in using digital technology in various humanistic investigations. To do so, they came up with the neologisms we enjoy today—awful phrases like e-scholarship and digital scholarship.Having said that, I do view the term digital scholarship basically as shorthand for the entire body of changing scholarly practice, a reminder and recognition of the fact that most areas of scholarly work today have been transformed, to a lesser or greater extent, by a series of information technologies: High-performance computing, which allows us to build simulation models and to conduct very-large-scale data analysis Visualization technologies, including interactive visualizations Technologies for creating, curating, and sharing large databases and large collections of data High-performance networking, which allows us to share resources across the network and to gain access to experimental or observational equipment and which allows geographically dispersed individuals to communicate and collaborate; implicit here are ideas such as the rise of lightweight challenge-focused virtual organizations
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We now have enormous curated databases serving various disciplines: GenBank for gene sequences; the Worldwide Protein Data Bank for protein structures; and the Sloan Digital Sky Survey and planned successors for (synoptic) astronomical observations. All of these are relied upon by large numbers of working scientists. Yet the people who compiled these databases are often not regarded by their colleagues as "real" scientists but, rather, as "once-scientists" who got off-track and started doing resource-building for the community. And it's true: many resource-builders don't have the time to be actively doing science (i.e., analysis and discovery); instead, they are building and enabling the tools that will advance the collective scientific enterprise in other, less traditional ways. The academic and research community faces a fundamental challenge in developing norms and practices that recognize and reward these essential contributions.This idea—of people not doing "real" research, even though they are building up resources that can enable others to do research—has played out as well in the humanities. The humanists have often tried to make a careful distinction between the work of building a base of evidence and the work of interpreting that evidence to support some particular analysis, thesis, and/or set of conclusions; this is a little easier in the humanities because the scale of collaboration surrounding emerging digital resources and their exploitation for scholarship is smaller (contrast this to the literal "cast of thousands" at CERN) and it's common here to see the leading participants play both roles: resource-builder and "working" scholar.
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Interesting short piece on challenges of digital scholarship
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