What is Sage Data?
Data Planet is a web-based teaching and learning application that provides fast and easy access to data from licensed and public domain datasets within an easy-to-use interface. With this dynamic tool, you can scan the contents of the collection, select subjects and variables of interest, and view your data in side-by-side tables and charts.
The Data Planet repository contains more than 65 billion datasets sourced from 90+ source organizations. There are billions of charts, maps, views, rankings, time series and tables available for use in the Data Planet repository. All of the data have been standardized and structured, and are described with up to 37 fields of metadata, including a controlled vocabulary.
Statistical Datasets has a basic module and several premium datasets. Click here for a listing of datasets and sources available in the repository.
The premium datasets are:
What Datasets are Included in Sage Data?
To see which datasets are included in Data Planet, go to the Data Planet home page and view the "Browse Data by" section to see which Subjects and Sources are available to begin your search.
Subject Browse:
Source Browse:
All datasets are also visible within the "Datasets" page using tabbed browsing via the left-hand navigation:
If your institution subscribes to any premium datasets, they will appear in the left-hand navigation on the "Featured" tab, as well as within the appropriate Subject and Source tab listings..
For a full listing of datasets available in Data Planet Statistical Datasets, and the sources of these datasets, see Data Planet Datasets and Sources.
Selecting Data
There are multiple ways to find data. From the home page, select one of the options pointed out in the image below:
Selecting the Datasets link in the top menu of the home page, and the Browse by Subject or Source options all follow a similar navigation to land on a dataset of interest. For example, after selecting the Datasets link in the top menu of the home page, the following pathway opens:
1. A listing of the Browse by Subject options display
2. After selecting an area of interest, here, Education, a listing of databases appears that have statistics related to education.
3. After selecting a database of interest, here Applications and Admittances - Postsecondary Institutions displays a listing of datasets within this database.
From the listing of datasets, select one of interest, and presto - a chart opens to the right:
Using the Search Box
Use the search box in the Data Planet header to query the repository for topics of interest. In the example below, "Brazil" is entered into the search box.
After you run the search, a listing of results opens. Scroll the results to select a dataset of interest, which will return you to that specific data and chart. You can also filter results to the left of the results listing to narrow results by subject terms, source, database,and geography.
After selecting the data, you can display that data in a number of ways. By selecting one of the four icons in the central tool bar, you can show the data as trends over time, a comparative ranking, a map, or a pie chart.
Chart Options provides several alternatives for the style of the visualization, depending on whether you have selected Trend, Map, Rank, or Pie Chart. The example below shows options for Trend Views:
The Rank By option, where available, allows you to choose the criteria for ranking, as in this example, where "personal consumption expenditures" can be ranked by state, indicator, or specific line item within the selected indicator:
The Show/Hide Data option allows you the choice of displaying or not displaying data values with the visualization. Another option on the tool bar is the Calculator button that allows you to create formulas based on the data values selected and define new columns for displaying the calculated new values. For example, in the infographic below, a new column has been created using the Calculator that shows the difference from prior year in the value of platinum. For more on the Calculator, see Interface Tips and Tricks #13.
Output Types
There are many ways to deliver data from Data Planet Statistical Datasets using the Export button located on the menu bar:
The options allow you to export data for manipulation in other programs, infographics for use in work products, and pdfs of data views, and more.
Export Data
If you want to export the underlying data, use Excel, Delimited Text, SAS, or XML options. All of these options allow users to download the data into different programs (spreadsheets and a statistical software package) and manipulate it there. If you have used the Calculator feature to create formulas for additional data points, these data points are downloaded, as well.
The option to download to a Shapefile (only available for map views) allows users to export the map information to software that displays maps to ESRI requirements.
If you need to export data for importing into statistical software program(s), consult the documentation provided for that program. Available export formats for Data Planet Statistical Datasets include Delimited Text, Excel, and SAS, which can be imported into these common software programs, as below:
SPSS (Delimited Text and Excel)
SAS (SAS)
STAT (Excel)
Please let us know if there are other programs you use that it would be helpful for us to export. Contact us here
Images
There are four options for exporting the charts you create and the accompanying descriptions:
Export Option: Permanent URL Links
Export options include permanent URL links to views and/or associated data. These links differ from the Create DOI URLs in that the latest available data will be returned via the URL links if the more current date is selected whereas DOI links return to the exact view of the data at the time it was created. To explore options, open the Export icon on the center tool bar:
Four URL link options are provided:
Exporting Formatted Citations
The “Cite This” icon, circled in red below, in the center tool bar of the Data Planet interface, provides options for direct export of citations formatted for several popular style guides, as well as options for export to citation management programs.
Available options include:
Click on the Quotation Marks and select your preferred format. A dialog box will open with the formatted citation. “Copy to Clipboard” and then paste into your own document.
As with all electronic reference management tools, do note that the final responsibility for the citation is yours - as the author of the paper - so be sure to review the citation created against the source style guide and/or consult faculty. For more on Data Citation formats and exports in Data Planet, click here . Note that exports for reference manager software will require manual intervention to properly format for the style manual you are using.
More on Embeds
Data Planet users can create interactive embeds of Data Planet content that can be added to your web applications – a website, a LibGuide, a WordPress blog - to enrich and enliven your own content! Embeddable data visualizations, available via the export menu in the Data Planet data viewer, are available for all chart types in Data Planet, which include trends, rankings, pie charts, and maps. The embed feature is available for all non-rights restricted content (for any restricted content, the embed option will not appear in the Export drop-down menu).
The Data Planet embed provides many interactive elements, including:
The embeds contain the full source information for the underlying data, including a direct link back to the data source, as well as an expandable menu detailing the source, dataset, and citation information. Clicking on the “Data Planet” logo within an embed will take authorized (and authenticated) Data Planet users directly back to the dataset within the Data Planet interface, allowing them to further investigate and manipulate the data as they choose.
We have also added a capability for embed creators to choose “static” or “dynamic” embeds, both of which offer the interactive elements described above.
→ Selecting Static embeds ensures that all data within the embed remains the same as at the time the embed was created.
→ Dynamic embeds will update with new data as it is added to Data Planet – meaning your web application stays current with newly available or recast data.
Log into Data Planet, select the Embed option to the right in the center tool bar (see image above). A dialog box appears:
Copy the HTML code that is generated and insert into the page source of your web application, and voila! An embed!
Data Planet comes with a robust - and easy-to-use - mapping feature. Data Planet maps are powered by Google Maps API, which allows for precise rendering of map images based on user geography selection and zoom level. Users are able to choose from several basic map types: thematic or terrain maps or satellite. Quickly move back and forth between views to decide on the view that best communicates the point you're trying to make.
The large +/- sign on the lower right of the map image can be used to zoom in for map detail or out to take a bird's eye view. Use the expand/contract icon on the upper right of the map image to view - you guessed it - in full screen, and easily toggle back to the window view.
1. From the Help button on the top tool bar, access the Data Planet Accessibility Toolkit, an FAQ page, and the complete library of Data Planet search guides. Your library has the option of adding additional links, so some of you may also see a Chat or other options:
2. Compare multiple datasets using the Compare Data option. Clicking on the option opens checkboxes in the listing of datasets, as below:
3. When comparing datasets, use the Filter option to toggle between the selected datasets and make new selections to further modify your chart:
4. Use the search box in pop-out windows to quickly land on an item of interest:
5. Send your visualizations and data to colleagues, faculty, and students by creating permanent links (DOIs), using the "Create DOI link" that appears below the charts. The URL link provided ensures that the person viewing it will see the exact version of the chart at the time you created it.
6. Find options for visualizing and customization of your charts in the Chart Options link below the center tool bar. Each chart type offers different options. Below you'll see the options for Rank charts:
7. Hovering over an item in the chart legend makes that item less prominent in the chart. If you click on an item, it will be removed from your chart view.
8. View the underlying data by clicking on the Table link in the center tool bar. And so many options when you do!
1. Export data to a preferred file format.
2. Toggle between ascending and descending row order by clicking on the column heading.
3. Search within data values in the table using precise search options.
9. Find related data by clicking on the Subject Terms links in the descriptions below the visualizations:
10. Interested in honing in on just a portion of a trend? Click on the beginning data point of interest and drag the cursor to the end point. Clicking on the "Reset zoom" option will reset the chart to the full trend.
11. Use the Calculator to derive new data values.
Click on the Calculator icon on the far right of the center tool bar. You can either type in your own formula or select a preformatted formula, as in the example below.
1. Create your indicator name.
2. Select the precision of the data value you are creating.
3. To select a preformatted formula, open the drop down menu in the Function bar.
After saving to the chart, a new data column displays in the chart, along with the new trend.
Sage Data Archiving Policy
Sage Data keeps datasets available for use and search even if the source provider is no longer updating them. In these cases, we append the dataset name with the notation “[Archive]” and add an explanation of why the dataset is no longer updated in the dataset description. In cases where the dataset has been licensed for use in Sage Data from a commercial or private source, the source provider may require that a dataset be removed entirely.
Sage Data Coverage Policy
The statistical datasets included in the Data Planet repository are added based on an evaluation and prioritization process that takes into account the following factors:
To identify new datasets for addition to the repository, the data development and editorial teams periodically assess gaps of coverage by subject area. In addition, government, nongovernmental, international, and other organizational websites and news releases are followed on an ongoing basis to identify new datasets for evaluation and potential addition to the repository.
Suggestions on datasets to add to Data Planet repository are always welcome! Please contact us at onlinesupport@sagepub.co.uk.
Datasets Available in Sage Data
Click on the links below to explore statistics available in Data Planet Statistical Datasets by broad subject areas:
| · Agriculture & Food | · Industry, Business, & Commerce |
| · Banking, Finance, & Insurance | · International Relations & Trade |
| · Criminal Justice & Law Enforcement | · Labor & Employment |
| · Education | · Military & Defense |
| · Energy Resources & Industries | · Natural Resources & Environment |
| · Government & Politics | · Population & Income |
| · Health & Vital Statistics | · Prices, Consumption, & Cost of Living |
| · Housing & Construction | · Transportation & Traffic |
For more detail on premium dataset offerings - including EASI Market Planner; China Data Center (subnational data); Claritas Consumer Profiles; Claritas Clout; Data Axle Reference Solutions: Historical US Business, Historical US Residential, and Historical Canadian Business; and Woods & Poole Complete U.S. Database
Sage Data Source Organizations
Lists sources included in the Data Planet repository categorized as International, Private/Commercial, or Public.
| Administrative Office of the US Courts | Intercontinental Exchange Benchmark Administration |
| Agency for Healthcare Research and Quality | Internal Revenue Service |
| Australian Bureau of Statistics | International Monetary Fund |
| Barchart | NASDAQ OMX Group (US) |
| BSE Limited (India) | National Bureau of Economic Research |
| Bureau of Economic Analysis | National Cancer Institute |
| Bureau of Justice Statistics | National Center for Education Statistics |
| Bureau of Labor Statistics | National Highway Traffic Safety Administration |
| Bureau of Transportation Statistics | National Oceanic and Atmospheric Administration |
| Center for International Comparisons of Production, Income and Prices | National Science Foundation |
| Centers for Disease Control and Prevention | Nikkei (Japan) |
| Children’s Bureau | Office of Management and Budget |
| China Data Institute | Office of Postsecondary Education |
| Claritas | OECD |
| Consumer Financial Protection Bureau | Quandl |
| Data Axle | Public Health Agency of Canada |
| Dave Leip's Atlas of US Presidential Elections | Recovery Accountability and Transparency Board |
| Defense Manpower Data Center | S&P Dow Jones Indices (US) |
| Deutsche Börse Group (Germany) | Shanghai Stock Exchange (China) |
| Easy Analytic Software Inc. (EASI) | Sharadar |
| Energy Information Administration | Social Security Administration |
| Environmental Protection Agency | Standard & Poor's (US) |
| European Centre for Disease Prevention and Control | Stevens Analytics |
| European Commission | Statistics Canada |
| Substance Abuse & Mental Health Services Administration | |
| Eurostat | United Nations |
| Exchange Data International | United Nations Economic Commission for Europe |
| Federal Bureau of Investigation | United Nations High Commissioner on Refugees |
| Federal Deposit Insurance Corporation | US Department of Agriculture |
| Federal Election Commission | US Department of Homeland Security |
| Federal Emergency Management Agency | US Department of Housing & Urban Development |
| Federal Financial Institutions Examination Council | US Department of Labor |
| Federal Housing Finance Agency | US Department of the Treasury |
| Federal Highway Administration | US Department of Veterans Affairs |
| Federal Housing Finance Agency | US Equal Employment Opportunity Commission |
| Federal Procurement Data System | US House of Representatives Office of the Clerk |
| Federal Reserve Board | US Senate Historical Office |
| Freddie Mac | US Office of Personnel Management |
| Groningen Growth and Development Centre | US Senate Office of Public Records |
| HSI Services Limited (Hong Kong) | Woods & Poole Economic, Inc. |
| Institute for Supply Management | World Bank |
| Institute of Museum and Library Services | World Resource Institute |
| World Trade Organization |
The inclusion of datasets in Data Planet from the sources listed here does not imply sponsorship, endorsement, recommendation, favoring or other association with SAGE, Data Planet, and/or any other SAGE products or services by any of the source organizations.
Data Planet offers eight premium modules as an add-on to the basic collection:
Finding Premium Datasets by Subject
To see if your library subscribes to any of these modules, look in the indicator panel (the panel on the left side) in Data Planet Statistical Datasets. If available at your library, you will see the datasets listed both by Subject and Source, as below:
Terminology Basics
Below you will find simple definitions of the basic terminology associated with data and statistics. From the examples below you can link into Sage Data to explore the millions of datasets available in the repository.
|
Sage Data publishes aggregated secondary datasets: Secondary means that the data are collected by source organizations other than Sage Data. Secondary data are contrasted with primary datasets, which refer to data that researchers have collected themselves. Aggregated means simply that the datasets are a collection of summary data, vs microdata, which refer to the individual response items in surveys and other data collection instruments. |
Data: Fundamentally, data=information. We typically use the term to refer to numeric files that are created and organized for analysis. There are two types of data: aggregate and microdata.
Data point or datum: Singular of data. Refers to a single point of data. Example: 25,114 billion BTU of aviation gasoline was consumed by the transportation sector in the US in 2012
Quantitative data/variables: Information that can be handled numerically. Example: spending by US consumers on personal care products and services
Qualitative data/variables: Information that refers to the quality of something. Ethnographic research, participant observation, open-ended interviews, etc., may collect qualitative data. However, often there is some element of the results obtained via qualitative research that can be handled numerically, eg, how many observations, number of interviews conducted, etc.
Indicator: Typically used as a synonym for statistics that describe something about the socioeconomic environment of a society, eg, per capita income, unemployment rate, median years of education.
Statistic: A number that describes some characteristic, or status, of a variable, eg, a count or a percentage. Example: total nonfarm job starts in August 2014
Statistics: Numerical summaries of data that has been analyzed in some way. Example: ranking of airlines by percentage of flights arriving on-time into Huntsville International Airport in Alabama in 2013
Time series data: Any data arranged in chronological order. Example: Gross Domestic Product of Greece, 2000-2013
Variable: Any finding that can change or vary. Examples include anything that can be measured, such as the number of logging operations in Alabama.
Terminology Used with Collections of Data
Data aggregation: A collection of datapoints and datasets. Example: a search on the broad category "higher education" in Data Planet retrieves results from a collection of sources.
Dataset: A collection of related data items, eg, the responses of survey participants. This term is used very loosely – the entire Census 2010 Summary File 1 can be considered a dataset as can any individual table published in the Census 2010 Summary File 1, eg, Table P20. Households by Presence of People Under 18 Years by Household Type by Age of People Under 18 Years
Database: A collection of data organized for research and retrieval. Example: American Community Survey.
Time series: A set of measures of a single variable recorded over a period of time. Example: Hourly Mean Earnings of Civilian Workers – Mining Management, Professional, and Related Workers
"Big Data" Terminology
Big data: A popular term used across academia, industry, and other arenas to describe the increased availability of all types of data. Big data is typically described as being huge in volume, high in velocity (how fast it is created, and diverse in variety.
Data analytics: Generally used to refer to the analytical techniques and tools required to analyze massive amounts of data.
Definition References:
Cramer, D., & Howitt, D. (2004). The SAGE dictionary of statistics (Vols. 1-0). SAGE Publications, Ltd. https://doi.org/10.4135/9780857020123
Herzog, D. (2015). Data literacy: A user’s guide. SAGE Publications, Inc. https://doi.org/10.4135/9781483399966
Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures & their consequences. SAGE Publications Ltd. https://doi.org/10.4135/9781473909472
Vogt, W. P. (2005). Dictionary of statistics & methodology.SAGE Publications, Inc. https://doi.org/10.4135/9781412983907
To see which datasets are included in Data Planet, go to the Data Planet home page and view the "Browse Data by" section to see which Subjects and Sources are available to begin your search.
Subject Browse:
Source Browse:
All datasets are also visible within the "Datasets" page using tabbed browsing via the left-hand navigation:
If your institution subscribes to any premium datasets, they will appear in the left-hand navigation on the "Featured" tab, as well as within the appropriate Subject and Source tab listings..
For a full listing of datasets available in Data Planet Statistical Datasets, and the sources of these datasets, see Data Planet Datasets and Sources.
Terminology
Data visualization: Any tool or technique for representing data visually.
Infographics: Formatted displays that provide a data visualization and textual content.
DataSheet: Term used by Data Planet to describe the formatted infographics that can be created using the time series and visualization tools available in the Data Planet repository, which are served up with rich metadata content describing the data displayed. All DataSheets can be exported to pdf and inserted into your work products. Example:
Basic Trend:
Map:
Ranking:
Other options include area, bar, line, doughnut, vertical or horizontal stacked, funnel, and pyramid charts. The powerful functionality of the Data Planet Statistical Datasets platform also allows the creation of charts trending multiple indicators, using the "compare" feature.
A reference list citing the sources used in preparing a research paper or work product is generally required. Citing sources serves several purposes, including
Failure to provide attribution to the sources consulted in preparing a research is considered evidence of plagiarism, that is, the presentation of others’ work as your own.
As with other electronic resources, citing datasets and infographics presents certain challenges and standards are evolving in this area.
There are many valuable resources to help you construct a properly formatted citation. Your first resource should be the style manual guide for the specific style required for your research paper or work product. Consult your faculty, writing center, or library for more information.
A great resource on Data Citation is available through IASSIST (International Association for Social Science Information Services and Technology). Click here to access the IASSIST Quick Guide to Data Citation.
At Data Planet, we follow the lead of DataCite, a global network of dataset researchers, whose goal, as stated on their website, is “to help make data more accessible and more useful; our purpose is to develop and support methods to locate, identify and cite data and other research objects.”
Toward that end, Data Planet utilizes Digital Object Identifiers (DOIs). DOIs are assigned to each DataSheet created. The DOI ensures that the same version of the data and infographic can be retrieved at any point in future. For more on DOIs, click here .
DataCite recommends the following elements be included in a citation to a dataset:
Creator (PublicationYear). Title. Version. Publisher [or Distributor]. (ResourceType.) Identifier
All DataSheets created in Data Planet include a citation in the DataCite preferred format:
Example:
Organisation for Economic Co-operation and Development (OECD) (2018-04-06). Main Economic Indicators (MEI): Finance | Country: Argentina | Indicator ID: CCUS, 01/1959 - 12/2017. Data Planet™ Statistical Datasets: A SAGE Publishing Resource. (dataset). Dataset-ID: 062-003-004. https://doi.org/10.6068/DP163F9ED671E6
Data Planet Statistical Datasets currently supports exports to the reference management tools RefWorks, EndNote, and Zotero.
Do note that the final responsibility for the citation is yours - as the author of the paper - so you should always review the citation created using a reference manager against the source style guide. Consult your faculty, writing center, or library for more information.
While DataCite is the standard, not all style manuals have adopted it, nor have all style manuals set guidelines for data citation. Below we provide examples of commonly used citation formats for datasets and views you create in Data Planet Statistical Datasets.
Two caveats:
1. Data Planet datasets and views use DOIs as a permanent and unique identifier - ensuring that you can always return to the dataset and the view at the time you created it. For more on DOIs, visit here. When citing sources, you will sometimes see a DOI displayed without a URL, eg, as DOI: 10.6068/DP17F756C78B333. The organizations that issue DOIs encourage use of the URL and we do too: eg, https://doi.org/10.6068/DP17F756C78B333.
2. As with all electronic reference management tools, do note that the final responsibility for the citation is yours - as the author of the paper - so be sure to review the citation created against the source style guide and/or consult faculty.
****NEW****
American Psychological Association style (7th edition)
Format: Author/Producer. (YYYY, Month Day). Dataset title: chart title version [Data set]. Publisher Name. https://doi.org/xxxxx
Example: Energy Information Administration. (2020, May 17). Retail gasoline prices: Gasoline prices - all grades, 08/20/1990 - 05/11/2020 [Data set]. Data Planet™ Statistical Datasets: A SAGE Publishing Resource. https://doi.org/10.6068/DP1722EF40B2064
****
American Psychological Association style (6th edition)
Format: Author/Producer. (Year, Month Day). Title of dataset (Version number) [Description of form]. Publisher. DOI [or Retrieved from URL.].
Example: Energy Information Administration. (2020, May 17). Retail gasoline prices: Gasoline prices - all grades, 08/20/1990 - 05/11/2020 [Dataset]. Data Planet™ Statistical Datasets: A SAGE Publishing Resource. 004-004-001. https://doi.org/10.6068/DP1722EF40B2064
Chicago author-date style (17th edition)
Format: Source. Publication Date. Title of Dataset. Publisher. DOI
Example: Energy Information Administration. 2017, September 5. Retail Gasoline Prices: Retail Gasoline Prices - All Grades, 08/20/1990 - 08/24/2017. Data Planet Statistical Datasets: A SAGE Publishing Resource. https://doi.org/10.6068/DP15E5374E97A17
MLA style (8th edition)
Format: Author. Title of Dataset (including date range of dataset). Publisher, Publication Date. Database Name, DOI.
Example: Energy Information Administration. Retail Gasoline Prices: Retail Gasoline Prices - All Grades, 08/20/1990 - 05/30/2016. Data Planet Statistical Datasets: A SAGE Publishing Resource, 17 Sept. 2017. https://doi.org/10.6068/DP15E5374E97A17.
What are DOIs?
DOIs, or Digital Object Identifiers, are used to identify content objects in the digital environment. They provide an actionable, interoperable, persistent link of an object, which can be any entity (thing: physical, digital, or abstract). DOIs, as defined by the International DOI Foundation, are:
DOIs mean that the same version of an article, image, dataset, graph, etc., can be retrieved at any point in future.
Key Concepts
DOI = Digital Object Identifier
IDF = International DOI Foundation, the operating and governing organization: https://www.doi.org/
RAs = DOI Registration Agencies, which are members of IDF offering the system to customers who wish to assign DOI names
DOIs are structured as a unique alphanumeric string assigned to a digital object. In Data Planet, DOIs are assigned by the DataCite RA and each DOI is associated with a set of basic metadata and a URL pointer so that it uniquely identifies the content item and provides a persistent link to its location on the internet.
Official Documentation
Website: https://www.doi.org/
DOI® Handbook – main source of definitive information
Factsheets – coverage of selected topics in detail
Printable Guide to DOIs in Sage Data
First select the indicator(s), variables, and chart, map, graph, or ranking that you wish to save for viewing later, citing in your research, or including in your work product. (For more information on searching and manipulating the data in Data Planet Statistical Datasets, click here. ) Below is a trend showing median household income in three US states:
Notice that below the infographic on the right, there is an active link labeled "Create Link (DOI)". Click to generate a DOI. (If a DOI has already been created for this particular view, an actual DOI will display rather than "Create Link (DOI)".) After you Create the DOI, the statistical abstract that appears below the infographic is updated to display the DOI in the same spot where "Create Link (DOI)" had appeared. This link can be copy and pasted into your work product, an email, etc. Using this link ensures that the person you provide it to will see the same view of the data that you selected. The DOI is included with all export options in Data Planet.
The DOI also appears in the citation of the view - you should always include the DOI when you cite a view in your papers. It is acceptable to shorten the DOI using the shortDOI® Service made available by the International DOI Federation. Enter the base DOI (eg, 10.6068/DP16F86DB812921) at the site and the service will either create a new shortDOI, or return the existing shortDOI if one has already been created. Applications that resolve DOI names will treat the shortDOI identically to the original.