Is it possible for scholars to scan the rapidly growing corpus of scholarship available on the open web? How can communities identify relevant and timely materials and share these discoveries with peers? Anyone who tries to stay current with new research and conversations in their field -- ourselves included -- faces an overwhelming amount of material scattered across the web. For the past three years the PressForward team has been experimenting with methods for catching and highlighting web-based scholarly communication by concurrently developing our Digital Humanities Now (DHNow) publication and our PressForward plugin for WordPress. Read about how we prototyped a scalable and reproducible publication model here.
Seven issues. Nearly 90 works by over 120 authors and a half dozen institutions. More than 600 pages. Who says that there is no scholarship on the open web? With the first two volumes of the Journal of Digital Humanities (JDH) we have offered an overlay journal for this diverse and emerging field, sourced almost entirely from scholarship on the open web in the previous six months. This post provides background on some frequently asked questions about the production of JDH content and issues.
Over the past four years, Digital Humanities Now (DHNow) has used a variety of approaches to aggregating, reviewing, selecting, and disseminating scholarly content from the open web. By experimenting with DHNow, we are developing methodologies and technologies to facilitate community-sourced publications beyond digital humanities. In this post we detail some of the methods and technologies we have used along the way and our wishlist and plans for the future.
Do visitors to the websites of professional scholarly associations and communities actually find any scholarship? This report by Caitlin Wolters, a George Mason MA Student and intern at PressForward, assesses the scholarly communication available on the websites of twelve professional associations and communities from the sciences and the humanities. Report
In this report Xin Guan, a graduate student of computer science at George Mason University, introduces the Support Vector Machine (SVM) program he developed to identify valuable pieces from the large pool of potential content for Digital Humanities Now. Those interested in the concepts and logistics behind the classifier program will be interested to read his explanation of the Active Learning method of Machine Learning he used. Report
Sixteen months after the relaunch of Digital Humanities Now, it is time again to offer a glimpse behind the scenes. While many of the trends we identified in our six month report remain stable, there have been two significant changes in our editorial process. First, we have reduced our publication cycle from daily to twice weekly. Second, we have expanded our editorial team to include 121 Editors-at-Large from the digital humanities community.
It has been six months since Digital Humanities Now relaunched in version 2.0 through the support of the PressForward Project, funded by the Sloan Foundation. The first version, run between 2009 and 2010, was an automated survey of Twitter. Version 1.5 was a one-man operation by Dan Cohen to vet the material using traditional methods of... Read more »
After five months of retooling, we’re relaunching Digital Humanities Now today. As part of this relaunch it has been moved into the PressForward family of publications, as one of that project’s new models of how high-quality work can emerge from, and reach, scholarly communities. The first iteration of DH Now, which we launched two years... Read more »