Skip to main content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
Library Databases for Statistics
*Lehigh subscription.* Aggregates statistical data on over 600 international industries from more than 18,000 sources, including market researchers, trade organizations, scientific journals, and government databases.
Data-Planet Statistical Datasets
*Lehigh subscription.* Search datasets from public and private sources, covering 16 subject areas.
*Lehigh subscription.* Access to a mix of company, industry, country and financial data for every major marketplace in the world.
*Lehigh subscription.* Full text of OECD Books, Papers and Statistics and the gateway to OECD’s analysis and data. 1998 to present.
Find international statistics collected by the United Nations and related organizations.
World Bank Data
Development statistics by country, topic and indicators
Data visualization and analysis tools
Datasets in the Social Sciences
This library guide will give you an overview of how to find and use datasets in the social sciences. Click on the image below to be taken to the Datasets for the Social Sciences library guide.
Data Planet Libguide
The Data-Planet Libguide offers detailed information on how to use the resource. From the different datasets available to how to manipulate data. If you not familair with Data-Planet take a few moments to learn some of the finer points.
Why do we need data citation?
Datasets generated in the research are equally valuable as the papers appearing at scientific journals, and should be treated as a citable source on par with traditional materials. To ensure these dataset assets permanently available for access and reuse, the arising data citation can enable researchers to create links between their academic publications and the underlying datasets.
What does a data ciation contain?
||Creator(s) of the dataset
||Whichever is the later of: the date the dataset was made available, the date all quality assurance procedures were completed, and the date the embargo period expired.
||As well as the name of the cited resource itself, this may also include the name of a facility and the titles of the top collection and main parent sub-collection (if any) of which the dataset is a part.
||The level or stage of processing of the data, indicating how raw or refined the dataset is.
||A number increased when the data changes, as the result of adding more data points or re-running a derivation process, for example.
|Feature name and URI
||The name of an ISO 19101:2002 'feature' (e.g. GridSeries, ProfileSeries) and the URI identifying its standard definition, used to pick out a subset of the data.
||Examples: 'database', 'dataset'.
||The organisation either hosting the data or performing quality assurance.
|Unique numeric fingerprint (UNF)
||A cryptographic hash of the data, used to ensure no changes have occurred since the citation.
||An identifier for the data, according to a persistent scheme.
||A persistent URL from which the dataset is available. Some identifier schemes provide these via an identifier resolver service.
What should researchers be aware of when citing a dataset?
Although the standardization and consistency in research data citation are still evolving, Ball and Duke(2012) from Digital Curation Center have summarzied some widely accepted practices in data citation for researchers to use:
- If you have generated/collected data to be used as evidence in an academic publication, you should deposit them with a suitable data archive or repository as soon as you are able. If they do not provide you with a persistent identifier or URL for your data, encourage them to do so.
- When citing a dataset in a paper, use the citation style required by the editor/publisher. If no citation style is suggested, take a standard data citation style (e.g. DataCite’s) and adapt it to match the style for textual publications.
- Give dataset identifier in the form of a URL wherever possible, unless otherwise directed.
- Include data citations alongside those for textual publications. Some reference management packages now include support for datasets, which should make this easier.
- Cite datasets at the finest-grained level available that meets your need. If that is not fine enough, provide details of the subset of data you are using at the point in the text where you make the citation.
- If a dataset exists in several versions, be sure to cite the exact version you used.
- When you publish a paper that cites a dataset, notify the repository that holds the dataset, so it can add a link from that dataset to your paper.
(Adapted from "Alex Ball and Monica Duke, 2012. How to Cite Datasets and Link to Publications. In A Digital Curation Center 'working level' guide. Digital Curation Center".)