Web Science and Digital Libraries Research Group

Mat Kelly taught CS418 - Web Programming at Old Dominion University in Spring 2015. This blog post highlights some teaching methods and technologies used (namely, Docker and GitHub) and how he integrated their usage into the flow of the course.                            For Spring Semester at Old Dominion University I taught CS418 - Web Programming with some updated methods and content. This course has been previously taught by various members of ODU WS-DL ( 2014 , 2013 , 2012 ). The first deviation from previous offerings of the course was to change the subject of the project. Previously, CS418 students were asked to progressively build an online forum like phpBB . Web sites resembling this medium are no longer as common as they once were on the Web, so a refresh was needed to keep the project familiar and relevant. For Spring, I asked students to build a Question-and-Answer website akin to StackOverflow.com . Being students of computer science, all were familiar with the c

For over 1 year, Hany SalahEldeen's Carbon Date service has been out of service mainly because of API changes in some of the underlying modules on which the service is built upon. Consequently, I have taken up the responsibility of maintaining the service, beginning with the following now available in Carbon Date v2.0. Carbon Date v2.0 The Carbon Date service currently makes requests to the different modules (Archives, backlinks, etc.), in a concurrent manner through threading. The server framework has been changed from bottle server to CherryPy server which is still a python minimalist WSGI server, but a more robust framework which features a threaded server. How to use the Carbon Date service There are three ways: Through the website, http://cd.cs.odu.edu/ : Given that carbon dating is highly computationally intensive, the site should be used just for small tests as a courtesy to other users. If you have the need to Carbon Date a large number of URLs, y

(note: Carbon Date 2.0 was released on 2014-11-14 ) In the course of our research we often needed to determine when a certain web resource was created. In numerous cases, this question is fairly straightforward to answer by examining the resource itself. Articles often have publishing datetime stamps, social media contributions have posting time, and others you can estimate the creation date from reading the resource itself. This process is simple upon manually examining the resource, but when the dataset of resources is large it is harder to automate. To solve this problem we conducted several experiments to determine when the resource was created automatically. When a resource is created it often gets indexed in the search engines, archived in the public archives, and shared in the social media thus leaving trails of existence. We trace those trails of existence and use the first appearance of the first trail as a close estimate of the creation date. The timeline below illustra