Below is a selection of sources of data and statistics available for researchers and students at the University of Oxford. To see more sources, and find out about services for those who need to make secondary use of statistics and data, go to the the Bodleian Data Library.
For a comrehensive list of business resources see The Sainsbury Library: Key Business Resources libguide.
A financial market intelligence database that replaces Thomson Reuters’ previous products ‘Datastream’ and ‘Thomson One’ now available on one desktop workstation in the “SSL Data Area”.
It provides information on markets, indices, company and economic information and historical financial data. It provides access to trusted, up to the minute and accurate content from more than 5 million securities world-wide. Coverage includes Pricing Data, Research, Fundamentals, Financial Estimates, News and Charts.
More information is available on SOLO and on directly from Thomson Reuters along with their training materials. Guides are available in the SSL Data Area or to download from the SSL website guides section.
This longitudinal national dataseries provides ranges of annual data from 1815 to the present for over 200 countries with 196 variables with comprehensive listing of international and national country data facts. General categories include demographic, social, political, and economic topics.
For more information about the dataset go to the publisher's site.
The largest resource for Indian statistical data on health, higher education, agriculture, economic statistics and tourism related data et al.
Note: We only have a ONE user licence, so please logout as soon as you have finished.
UK economic activity covering production, distribution, consumption and trade of goods and services. Individuals, businesses, organisations and governments all affect the development of the economy.
A population database that maps geographical distribution of a populace within cells of one-kilometre resolution over a 24 hour period. This allows assessment, estimation and visualisation of populations reacting to disease outbreaks, social upheaval or natural disasters. The modelling process uses sub-national level census counts and other data for each country combined with high resolution imagery analysis.