Research Support Services

Temple University Libraries are committed to supporting faculty and graduate students as they discover new knowledge and seek to disseminate their findings in ways that both acknowledge their individual contributions and have the broadest possible impacts in their fields.

Researcher Networking

Discover other researchers at Temple and other institutions who may be potential collaborators.

  • Pivot (from Community of Science)
    Pivot includes info about sponsors in many disciplines, and includes federal, non-federal, and international sponsors. Jointly funded by the Libraries and Research Administration.
  • Microsoft Academic Search (free)
    A remarkably extensive profiling system with worldwide reach, it is not dependent on institutional subscriptions to services such as Pivot or SciVal Experts.

Discover Funding Opportunities

  • Pivot (from Community of Science)
    Pivot includes info about sponsors in many disciplines, and includes federal, non-federal, and international sponsors. Jointly funded by the Libraries and Research Administration.
  • SPIN funding alerts through eRA@TU (Electronic Research Administration)
    eRA @TU is Temple University's online research administration system, encompassing both pre- and post-award processes that involve the administrative and regulatory aspects of grants, contracts and clinical trials.
  • Egrants.net (requires creating a free user account)
  • Foundation Directory Online (funded by Temple University's Office of Institutional Advancement and Office of Research)
    FDO provides subscribers with access to information on grantmakers and their grants, including a database of over 140,000 foundations, corporate giving programs, and grantmaking public charities in the U.S., and over 4,000 sponsoring companies.

Plan to Manage Your Data (required for many grants):

NSF, NIH and many other federal and private funding agencies require researchers submit data management plans with their grant applications. Having a data management plan is also just good scholarship.

Publish Findings and Disseminate Data...

Understand How to Cite Data

Data citation is an important component of data sharing and data reuse and is similar to the longstanding practice of citing scholarly articles and books. This will ensure your results can be replicated by access to the data used and will give the data creators credit for creating and sharing their work. Tools and publications have already been developed to track citations to data sets so that a scholar’s contributions and impact can be measured.

  • Always check with the journal in which you plan to publish for their data citation format. However, know that many journals and citation styles do not yet specifically require you to cite research data, or don't give specific citation guidelines for data sets. In this case, you should still cite any data you use in your analysis by using the following key elements as recommended by the Yale and MIT data citation guides:
    1. Author(s)
    2. Title
    3. Year of publication: The date when the dataset was published or released (rather than the collection or coverage date)
    4. Publisher: the data center/repository
    5. Any applicable identifier (including edition or version)
    6. Availability and access: URL or other location information for the data
  • See the MIT guide at: http://libguides.mit.edu/c.php?g=176032&p=1159520 or the Yale guide at: http://guides.library.yale.edu/content.php?pid=324929&sid=2665439
  • DataCite is an international organization that helps researchers to find, access, and use data. Their recommended data citation format is:
    • Creator (PublicationYear): Title. Version. Publisher. ResourceType. Identifier
  • For citation purposes, DataCite recommends that DOI names are displayed as linkable, permanent URLs as in the following examples: