Updated Feb 23, 2016 by Webmaster
In a rapidly changing technology environment it was only a matter of time that we would see some really cool things happening with 3D technology-particularly 3D scanning. University Library is embracing 3D scanning technology and finding ways to compliment the scanning initiatives that are already taking place with our cultural heritage and community partners. We recently purchased a portable Creaform GoScan scanner to begin capturing 3D artifacts.
Updated Feb 21, 2016 by Webmaster
Updated Feb 18, 2016 by Webmaster
As the head of Bibliographic and Metadata Services (BAMS), I coordinate the metadata creation for the vast array of digital collections produced by the IUPUI University Library Center for Digital Scholarship
. The involvement of catalogers in the process of metadata creation has brought an expertise in description to and enriched our digital collections. Additionally, this work has provided variety to the work of our catalogers and helped them to learn new skills that will take them into the future.
Updated Feb 08, 2016 by Metadata Librarian
Here’s a question I get at least a few times every month—I should really start keeping count … it goes something like this: “But I already have a ResearchGate profile, what’s the advantage of keeping other sites about my work up-to-date?” (Sometimes it’s “Academia.edu,” but less and less often on my campus.) It’s a hard question to answer. In part because it assumes so much—that RG is the baseline, that other sites have the same functions, that the advantages are comparable. It’s also a difficult question to answer because it’s often not the real question.
Updated Feb 06, 2016 by Webmaster
Love Your Data week is almost here! LYD16 is a week devoted to helping students take better care of their research data, whether it takes the form of photos, numbers, text, videos, code, or social media interactions. Students and librarians from more than 20 colleges and universities will participate by sharing their horror and success stories, tips, tools, and more. Join us for laughs, support, or help solving your data problem.
Updated Jan 27, 2016 by Webmaster
At their November 18, 2015 meeting, IUPUI Staff Council, an elected campus entity that, “represents the staff in the communication processes and decision making of the university. . .and promotes staff development and recommends policies which aid in retaining highly qualified personnel. . .” among many other activities, adopted an Open Access Statement of Support.
From the statement,
Updated Jan 27, 2016 by Webmaster
IUPUI ScholarWorks is an institutional repository. It's also a website ... which means that people come looking for our site with keyword searches, direct links, social media sharing and all the other awesome sauce that makes the Internet a busy place.
Updated Mar 27, 2016 by Scholarly Communications Librarian
Open access benefits scholars everywhere by connecting them to research they may not otherwise be able to access, but I'd like to take a moment to look at open access in reverse. By making my research open access, I benefit myself as well as the community at large. My work gets much wider exposure through my deposits in IUPUI ScholarWorks than it would ever receive confined to a single journal or conference. My 2012 article, “Opening Interlibrary Loan to Open Access,” has 415 file views from countries as diverse as the US, China, Italy, Ukraine, and Australia. The 2011 conference presentation on which it was based has 177 file views from an equally diverse set of countries. An earlier article, “Going Global: An International Survey of Lending and Borrowing across Borders,” has 156 file views.
The impact is even more apparent when you look at conference presentations.
Updated Dec 14, 2015 by Webmaster
Lately, I have been spending more time playing around with R. As an R beginner and someone interested in data visualization, one of my favorite packages so far is ggplot2. This package vastly simplifies the process of plotting data and the results are rather aesthetically pleasing. One of the really powerful features of ggplot2 is the way in which it makes visually encoding multiple dimensions of a dataset much easier.
In this brief tutorial, I will plot some data generated using Excel. The data (available here) represent 150 individuals and contains information on their gender, income, time spent commuting to work, student loans, and education level. I fabricated the data so that patterns will emerge in the resulting visualization that mimic what you might expect to see in the real world, but the data are totally fake.
The following presupposes some basic familiarity with R. If you are brand new, you may want to start with a basic R tutorial – there are dozens freely available on the internet.
Updated Mar 15, 2016 by Social Sciences & Digital Publishing Librarian