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NCI Request for Information on Existing Data Sharing Processes for NIH-Funded Research - due April 3

  • 1.  NCI Request for Information on Existing Data Sharing Processes for NIH-Funded Research - due April 3

    Posted 02-08-2023 17:09

    Special Announcements


    Request for Information on Existing Data Sharing Processes for NIH-Funded Research: The National Cancer Institute (NCI) is interested in understanding the processes for storage, preservation and sharing of scientific data generated by NIH-funded cancer research at academic, research and medical institutions in order to develop guidance on scientific data management. For more information, click here.

    Submission due: April 3, 2023



    ------------------------------
    Ken Schoppmann
    ABRF
    ------------------------------


  • 2.  RE: NCI Request for Information on Existing Data Sharing Processes for NIH-Funded Research - due April 3

    Posted 02-09-2023 09:12

    Thank you for posting Ken

     

    Frances

    (she/her)

     

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    Original Message


  • 3.  RE: NCI Request for Information on Existing Data Sharing Processes for NIH-Funded Research - due April 3

    Posted 02-09-2023 10:06

    Hi All,


    Please take a few moments and complete the NIH RFI questionnaire.  This questionnaire has three questions specific to cores/SRR.  Please complete this RFI, share it broadly at your institution, and help shape the NIH data science policies.  IT impacts every one of you.  

    And, although it comes from NCI, it is not just for NCI funded institutions and members.  This RFI will help inform all of NIH data science.  

    Core laboratories/SRR are major stakeholders in data management and sharing.  Our deliverable is data (metadata), contributing 50-90% of all research data for R1 institutions.  Cores inherently support transparency and have institutional responsibility for the conduct of research performed in their labs.  We are a central repository for institutional knowledge management, with core scientists with deep expertise in the strengths and limitations of technology and its applications.   We provide documented scientific workflows and data management plans to support data sharing and reproducibility, such as documenting who performed what experiment on which instrument, instrument standardization and maintenance, required controls, standards, documentation and tracking of buffers, reagents, components, lot numbers, version, expiration dates),  and the location of source data and shared data, thus ensuring data provenance.






    Original Message


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