Research @ Longwood: Find Datasets

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Digital Commons

Do you have a dataset you would like to save into our institutional repository? Please email digitalcommons@longwood.edu and we can help you save your data safely.

Data Management Plan

Funding bodies increasingly require grant-holders to develop and implement Data Management and Sharing Plans (DMPs).

Plans typically state what data will be created and how, and outline the plans for sharing and preservation, noting what is appropriate given the nature of the data and any restrictions that may need to be applied.

SPSS

Open Source Alternatives to SPSS

Can't afford or don't want to use SPSS? Try one of these open source alternatives. 

Statistics vs Data?

What is the difference between Data and Statistics?

In regular conversation, both words are often used interchangeably. In the world of libraries, academia and research there is an important distinction between data and statistics. Data is the raw information from which statistics are created. Put in the reverse, statistics provide an interpretation and summary of data.

Statistics

  • Statistical tables, charts, and graphs
  • Reported numbers and percentages in an article

If you’re looking for a quick number, you want a statistic. A statistic will answer “how much” or “how many”. A statistic repeats a pre-defined observation about reality.

Statistics are the results of data analysis. It usually comes in the form of a table or chart. This is what a statistical table looks like:

Table 1206. Adult Attendance at Sports Events by Frequency: 2007

Source: Statistical Abstract of the United States

 

Data

  • Datasets
  • Machine-readable data files, data files for statistical software programs

If you want to understand a phenomenon, you want data. Data can be analyzed and interpreted using statistical procedures to answer “why” or “how.” Data is used to create new information and knowledge.

Raw data is the direct result of research that was conducted as part of a study or survey. It is a primary source. It usually comes in the form of a digital data set that can be analyzed using software such as Excel, SPSSSAS, and so on. This is what a data set looks like:

Dataset example: each cell in the spreadsheet represents an individual response to survey questions

Getting Started with Data

Start by defining your topic

Be specific about your topic so that you can narrow your search, but be flexible enough to tailor your needs to existing sources.

Identify the Unit of Analysis

This is what you should be able to define:

#1 - Who or What?

Social Unit: This is the population that you want to study.
It can be...

  • People
    For example: individuals, couples, households
  • Organizations and Institutions
    For example: companies, political parties, nation states
  • Commodities and Things
    For example: crops, automobiles, arrests

#2 - When?

Time: This is the period of time you want to study.
Things to think about...

  • Point in time
    A "snapshot" or one-time study
  • Time Series
    Study changes over time
  • Current information
    Keep in mind that there is usually a time lag before data will be published.  The most current information available may be a couple years old.
  • Historical information

 #3 - Where?

Space: Geography or place.
There are two main types of geographic classifications...

  • Political boundaries 
    For example: nation, state, county, school district, etc.
  • Statistical/census geography
    For example: metropolitian statistical areas, tracts, block groups, etc.

Remember to define your topic with enough flexibility to adapt to available data!

Data is not available for every thinkable topic. Some data is hidden (behind a pay-wall for example), uncollected, unavailable. Be prepared to try alternative data.

Finding Data

Search Strategy #1: Search in a Data Archive

Look within a data archive that collects within the general subject area that you are searching for. There are several fee-based data archives, but there are many open access ones, such as:

Search Strategy #2: Identify Potential Producers

Ask yourself: Who might collect and publish this type of data?

Then visit the organization’s website and see if you're right! Or, search for them as an author in the library catalog.

These are some of the main types of data producers:

Government Agencies

The government collects data to aid in policy decisions and is the largest producer of data overall. For example, the U.S. Census Bureau, Federal Election Commission, Federal Highway Administration and many other agencies collect and publish data. To better understand the structure of government agencies read the U.S. Government Manual and browse FedStats. Government data is free and publicly available, but may require access through library resources or special requests.

Non-Government Organizations

Many independent non-commercial and nonprofit organizations collect and publish data that supports their social platform. For example, the International Monetary Fund, United Nations, World Health Organization, and many others collect and publish data. For more information about NGOs, visit Duke Libraries NGO Research Guide. Data from NGOs may be free or fee-based.

Academic Institutions

Academic research projects funded by public and private foundations create a wealth of data. For example, the Michigan State of the State Survey, Panel Study of Income Dynamics, American National Election Studies, and many other research projects collect and publish data. Much of this type of data is free and publicly available, but may require access through library resources. Access to smaller original research projects may be dependent upon contacting individual researchers.

Private Sector

Commercial firms collect and publish data as a paid service to clients or to sell broadly. Examples include marketing firms, pollsters, trade organizations, and business information. This information is almost always is fee-based and may not always be available for public release.

Search Strategy #3: Check the Literature

Search the Library for books and articles dealing with data. Some researcher include their data sets with their publications. If you need help doing this, please ask a librarian!

 

Attribution

Thanks to Hailey Mooney of Michigan State University Library for permission to reuse her content.