This webinar was prepared for and hosted by the SLA Social Science and Transportation divisions and the Upstate New York chapter. Presented on August 14, 2013.
Slide 1
14 August 2013
Data 101:A Gentle Introduction
Presented by
Kimberly Silk, MLS, Data Librarian, Martin Prosperity Institute,
Rotman School of Management, University of Toronto
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Our Agenda
Defining data librarianshipBasic terminologyCommon data
sourcesOur challenge: data management, preservation, discovery and
accessWhat are big data?What are data visualizations?SourcesQ &
A
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Defining Data Librarianship
Data librarianship is a relatively new area of practice,
emerging with the growth of digital media since the 1970s;Data
librarians are professional library staff engaged in managing
research data as a resource, and supporting researchers in these
activities;We support our institutions and researchers in the areas
of data management, metadata management, and teaching how to use
data as a resource;Many of us work in the social sciences, but
there is growth in the natural sciences and humanities as well.
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Basic Terminology
Data plural! Think: Squirrels!!
Microdata raw data, individual records consisting of rows of
numbers (Excel spreadsheet);Statistics summarized tables and
cross-tabulations that have been formulated from the raw
data;Aggregate data statistical summaries organized in a data file
structure (Excel) that permits further analysis;PUMF Public Use
Microdata File raw data that is available for public use; some data
may be filtered and geographies repressed to ensure personal
privacy;Variables a set of factors, traits or conditions that
describes a unit of analysis; for instance, sex, age, marital
status, etc.Frequencies the number of times an observation occurs
in the data;
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Common Data Sources
Govt- collected surveysUS Census (American Fact Finder)Bureau of
Labor Statistics, Bureau of Economic Analysis, Statistics
CanadaInternational sources such as UK Data Archive, Swedish
National Data Service, Australian Data Archive, etc.OECD iLibrary
World DataBankPew Research Center GallupThomson
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Other International Data Sources
Some countries do not gather data, have not been gathering data
for very long, or else limit or filter available dataFor instance,
Russia, India, China and other developing countries may not gather,
preserve or release their data;The BRICs (Brazil, Russia, India,
China) will struggle with this issue as their economies grow.
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Uncommon Data Sources
Data can come from everywhere;Occasionally, the MPI acquires
data from unusual sources, such as:Rolling Stone magazineMySpace
social media site for bandsCrunchBase database of technology
companies
Data Management, Preservation, Discovery & Access
Weve conquered print collections, but data present a new
challenge;Like all digital files, metadata is necessary to describe
data assets;Like images, a single data set can mean many things to
many people;How do we manage these data to make sure they are
discoverable, accessible, and preserved?Traditionally, data files
have been stored on network drives, and shared or restricted
according to the groups who need to use them;Network drives are
difficult to search, can be hard to share and restrict, and dont
deal with metadata well;Web pages with links has been a common way
to distribute data sets;We needed new tools a new kind of catalogue
that is designed for the specialized needs of data.
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Data Discovery Platforms
Nesstar developed in Norway by Norwegian Social Science Data
Services, used by Statistics Canada, UK Data Archive, NORC at the
University of ChicagoODESI proprietary system developed and used by
Scholars PortalDataverse Open source system developed by the
Institute for Quantitative Social Science (IQSS) at Harvard, used
by NBER and ICPSR
Dataverse
We installed an iteration of Dataverse at the University of
Toronto, in our cloud, and I manage my data collections myself;As
an open source solution, its cost-effective and my colleagues at
Scholars Portal support it for me and other Ontario
universities.The data are associated with studies; several data
sets can be associated with a single study;The world can see the
metadata for each data collection, but access to the data sets
themselves are restricted to those who contact me to get
permission.
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What are Big Data?
Big Data are data that are too large for the average database
management tool (Access and Excel, for instance).Examples come from
meteorology, genomics and physics. At MPI we wrestle with large GIS
data sets (maps and satellite data), and deal with data at the
terabyte (1 trillion bytes) level. Larger data sets deal with
petabytes (1 quadrillion bytes) and exabytes (1 quintillion
bytes).
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Data Visualizations
The visual representation of data ---- literally, a picture can
say a thousand [numbers]Edward Tufte is a key pioneer:
http://www.edwardtufte.com/tufte/Fantastic examples at Flowing
Data: http://flowingdata.com/ RSA Animate:
http://www.thersa.org/
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Sources
International Association for Social Science Information
Services & Technology (ASSIST) -
http://www.iassistdata.org/OECD iLibrary -
http://www.oecd-ilibrary.org/World Bank Data -
http://data.worldbank.org/UK Data Archive -
http://data-archive.ac.uk/Nesstar -
http://www.nesstar.com/Dataverse - http://thedata.org/
17 September 2012
Q & A
(and, Thank You!)
Kimberly Silk, MLS, Data Librarian, Martin Prosperity Institute,
University of [email protected]
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