background preloader

25 Awesome Beta Research Tools from Libraries Around the World

25 Awesome Beta Research Tools from Libraries Around the World
If you're tired of using the same old search box on your local library website for research projects, it might be time to broaden your horizons. Try out one of these in-the-works betas sponsored by world-class libraries around the world. From academic libraries like that at MIT or renowned research centers like the Library of Congress, the following beta research tools feature innovative tricks to connect you with the most relevant, valid results on the Internet and in their card catalogs. Melvil Dewey would be proud. Tools Used at College and University Libraries Check out this list for academically-minded beta search tools sponsored by universities around the world. Vera Multi-Search: MIT: This new tool is still in the works, but once it's officially approved, students and researchers can use Vera Multi-Search as a way to find material in several different databases with one single search.

Weft QDA - a free, open-source tool for qualitative data analysis Weft QDA is (or was) an easy-to-use, free and open-source tool for the analysis of textual data such as interview transcripts, fieldnotes and other documents. An excerpt from my MSc dissertation explains the thinking behind the software in more detail. The software isn’t being maintained or updated, but the most recent version is available for interest. Import plain-text documents from text files or PDF Character-level coding using categories organised in a tree structure Retrieval of coded text and ‘coding-on’ Simple coding statistics Fast free-text search Combine coding and searches using boolean queries AND, OR, AND NOT ‘Code Review’ to evaluate coding patterns across multiple documents Export to HTML and CSV formats Using Weft QDA The currrent version is 1.0.1, which was released in April 2006. it is not for major projects like a PhD thesis. For Windows Weft QDA 1.0.1 was developed for Windows XP, but may work on newer versions. Weft QDA download [2.66MB - version 1.0.1 - 26/04/2006]

Brooklyn Public Library - Local History Collections What's New Tweets by @Brooklynology Hours and Location Check out our Programs and Exhibitions page and the Brooklynology blog for more details. Contact Us Brooklyn Collection Central Library 10 Grand Army Plaza Brooklyn, NY 11238 Phone: 718.230.2762 Fax: 718.857.2245 Email: Ask a Librarian Image of the Week It took long enough, but Spring is finally here, and with it comes another baseball season. About the Brooklyn Collection The Brooklyn Collection is Brooklyn Public Library's local history division, providing a range of information and services about anything and everything Brooklyn. Photographs View and/or purchase more than 20,000 Brooklyn photographs. Digital Collections Brooklyn Collection 2.0 For a daily dose of Brooklyn history, follow the Brooklyn Collection on the Brooklynology blog, Twitter, and check out (and tag!) Brooklyn Connections Learn more about Brooklyn Connections, our unique research project partnerships for 6th through 12th grades. Meet the Brooklyn Collection

Self-Improving Bayesian Sentiment Analysis for Twitter That’s quite the mouthful. Let me start with a huge caveat: I’m not an expert on this, and much of it may be incorrect. I studied Bayesian statistics about fifteen years ago in university, but have no recollection of it (that sounds a bit like Bill Clinton: “I experimented with statistics but didn’t inhale the knowledge”). Even so, given the increasing quantity of real-time content on the Internet, I find the automated analysis of it fascinating, and hope that something in this post might pique your interest. Naive Bayes classifier Bayesian probability, and in particular the Naïve Bayes classifier, is successfully used in many parts of the web, from IMDB ratings to spam filters. The classifier examines the independent features of an item, and compares those against the features (and classification) of previous items to deduce the likely classification of the new item. It is ‘naïve’ because the features are assessed independently. 4 legs65kg weight60cm height DogHumanDog Classifying Sentiment

Digital Library for the Decorative Arts and Material Culture Think like a statistician – without the math I call myself a statistician, because, well, I'm a statistics graduate student. However, ask me specific questions about hypothesis tests or required sampling size, and my answer probably won't be very good. The other day I was trying to think of the last time I did an actual hypothesis test or formal analysis. I couldn't remember. I actually had to dig up old course listings to figure out when it was. It was four years ago during my first year of graduate school. Instead, the most important things I've learned are less formal, but have proven extremely useful when working/playing with data. Attention to Detail Oftentimes it's the little things that end up being the most important. The point is that trends and patterns are important, but so are outliers, missing data points, and inconsistencies. See the Big Picture With that said, it's important not to get too caught up with individual data points or a tiny section in a really big dataset. No Agendas Look Outside the Data Ask Why

The New York Art Resources Consortium (NYARC): Towards Radical Collaboration Librarians are natural collaborators—we share materials through interlibrary loan, data through cataloging cooperatives, and our subject and technical expertise on numerous listservs and professional committees—but moving beyond these traditional modes of collaboration is challenging. Collaboration is hard because it often requires an institutional shift; it is time-consuming and relies on effective communication, teamwork, consensus-building and a healthy dose of respect. Last week, Brooklyn Museum hosted a discussion on collaboration led by representatives from NYARC to talk about the future of art museum libraries and used the consortium’s activities as an example of how museum libraries are working together. Arcade launch party held in the Reading Room of the Frick Art Reference Library, February 24, 2009. From left to right: Ken Soehner, Arthur K Watson Chief Librarian at the Thomas J.

Social Network Analysis Social Network Analysis: Introduction and Resources What is Social Network Analysis? Network Data Collection and Representation Network Theories Analysis of Network Data Software Applications Books and Journals Article References Selected Online SNA Portals Ulrike Gretzel November, 2001 What is Social Network Analysis? Social network analysis is based on an assumption of the importance of relationships among interacting units. Actors and their actions are viewed as interdependent rather than independent, autonomous units Relational ties (linkages) between actors are channels for transfer or "flow" of resources (either material or nonmaterial) Network models focusing on individuals view the network structural environment as providing opportunities for or constraints on individual action Network models conceptualize structure (social, economic, political, and so forth) as lasting patterns of relations among actors Wasserman, S. and K. Scott, J., 1992, Social Network Analysis. Index Network Theories

Artforum Index The Artforum Index: Volume I, number 1, through volume VII, number 4 June 1962 through December 1968 1000 copies published 1 July 1970 as Artforum, 1962-1968: a cumulative index to the first six years by Laurence McGilvery, La Jolla, California. Corrections and new information about personal dates are welcome. This revised, free, on-line version published 1 November 2009. © 1970, 2002 & 2009 by Laurence McGilvery. Download The Artforum Index The High Performance Index: A partial, interim version © 2002 & 2009 by Art in the Public Interest Numbers 1-32 | Numbers 33-40 | Numbers 58/9-70 Priced list of available runs, single issues, and Astro Artz books and tapes on pp. 112-115 Numbers 42-57 and 71-6 not available at present This free, on-line index to over two-thirds of the issues has three sources. Numbers 1-32 (vols. 1-8, February 1978-1985) Numbers 33-40 (vols. 9-10, 1986-87) The index for numbers 58/9-69/70 was prepared for the publishers' own internal use.

SITE Monitoring Service