Access to machine readable numeric data files is provided at Columbia by the Electronic Data Service (EDS) which is a joint project of the Libraries and Columbia University Information Technology (CUIT). EDS was created to support the research and instruction at Columbia that requires the use of numeric data available only in machine readable form.
The program focuses on delivering numeric data resources to users in the Columbia community. Individual data resources, called data studies, can have many components and are formatted and delivered using a variety of techniques. EDS services include building the data collection (largely done by the Libraries), providing the technical support necessary to store and deliver the collection (largely done by CUIT), and assisting users with identifying and accessing studies (by both CUIT and Libraries). In support of this effort, we:
- participate in membership organizations that archive and/or distribute data or that support members by serving as forums for awareness of the trends and availability of data resources (organizations such as Inter-University Consortium for Political and Social Research (ICPSR), the National Center for Health Statistics (NCHS) Data Dissemination Program, Roper Center for Public Opinion Research, the Association of Public Data Users (APDU), and the New York State Data Center (SDC));
- support the use of data products received as part of the Federal Depository Library Program (FDPL);
- monitor the commercial and non-commercial markets for data products and select key data resources from these providers when they are not available through our membership organizations but are suited to our collection;
- participate with other interested groups within Columbia in an effort to promote awareness and use of GIS as an analytic tool;
- maintain a searchable catalog (DataGate) for those data resources we have in our collection;
- assist users in identifying data resources, whether they are in our collection or available elsewhere, and in manipulating that data into a format they will use in their work;
- support users in understanding the relationship among the parts of a data study: documentation (meta-data), raw data, and software applications needed to read the data;
- maintain a PC network with the software applications and space needed to deliver data products, both those that are received over the Internet and those that need a PC device.