This menu is intended to help researchers navigate the broad range of research support available on the IUPUI campus of Indiana University. It provides a listing of research data support services available to everyone at IUPUI, including IU-wide services, organized by stages of the research lifecycle. A brief description of each lifecycle stage is provided.
Note: Services available only to particular schools and departments are not listed here.
Provocation -- explore or mine open research resources and use open tools to network with colleagues. Researchers use the latest database and text mining tools to explore these resources, to identify new concepts embedded in the research, and to identify where novel contributions can be made.
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Ideation -- develop and revise research plans and prepare to share research results and tools under FAIR principles. When applying for research funding, they develop the required data management plans, stating where data, workflow, and software code will be available for use by other researchers under FAIR (Findable-Accessible-Interoperable-Reusable) principles. In addition, in some cases, they may decide to pre-register their research plans and protocols in an open repository.
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Knowledge generation -- collect data, conduct research using tools compatible with open sharing, and use automated workflow tools to ensure accessibility of research outputs. Researchers collect data, using tools that automate formatting and curation tasks to ensure that digital datasets are interoperable and documented. In the case of physical samples and specimens, such as rocks, ice core samples, or tissue samples, researchers develop concrete plans to archive these according to disciplinary best practices.
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Validation -- prepare data and tools for reproducibility and reuse and participate in replication studies. Researchers use open data techniques to analyze, interpret, and validate findings. They may present their preliminary findings at conferences and refine their methods based on relevant comments and critiques. They may deposit their initial working paper in a preprint server and revise the paper based on the open peer review afforded by the service. They prepare their data in standard formats according to disciplinary standards and describe both data and analytical code in optimal ways for reuse and replication.
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Dissemination: use appropriate licenses for sharing research outputs and report all results and supporting information (data, code, articles, etc.). Researchers select the best venue for open publication of their work, including articles, data, code, and other research products. They revise and, in some cases, substantially improve their work based on the comments of the peer reviewers. Upon acceptance and before final submission of their work, they select a public copyright license, such as the GNU General Public License for software or a Creative Commons license for other works, including scholarly articles.
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Preservation: deposit research outputs in FAIR archives and ensure long-term access to research results. Researchers deposit the final peer-reviewed articles in an openly accessible archive as required by their research funders. They deposit their research data and software in one or more data archives, with clear and persistent links among the article, data, and software. These FAIR data are then used by other researchers in the provocation phase of their own work.
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