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Research Data Management and Curation   Tags: data curation, data management, data sharing, dataverse network, dmp, dvn, sharepoint, virtual research  

This guide covers the research data management and curation resources available at the University of Alabama through a partnership of the UA Libraries, Office for Research, and Office for Information Technology.
Last Updated: Mar 10, 2014 URL: http://guides.lib.ua.edu/rdmp Print Guide RSS Updates

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Subject Guide

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Tom Wilson
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Thomas C. Wilson
Professor, Associate Dean
University Libraries

205-348-2299
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Help?

For assistance with data management plans, please email DMP Help.
 

What are Research Data?

The Office of Management and Budget, Circular A-110, defines data as:  

...recorded factual material commonly accepted in the scientific community as necessary to validate research findings, but not any of the following: preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues. This "recorded" material excludes physical objects (e.g., laboratory samples).
Research data also do not include: (A) Trade secrets, commercial information, materials necessary to be held confidential by a researcher until they are published, or similar information which is protected under law; and (B) Personnel and medical information and similar information the disclosure of which would constitute a clearly unwarranted invasion of personal privacy, such as information that could be used to identify a particular person in a research study.

In the Humanities and related disciplines, data could be text, text corpora, audio, image, or video.  

Academic departments and individual disciplines may add other designations.  

 

Important UA Links

This guide provides an introduction to resources in the University for Data Management Plan creation and execution. Use the tabs above or the links below to find information on the following topics:


UA Office for Research Links:

Research Data Management and Curation

What is this?

In a nutshell, data management and curation entails structured processes to ensure that the data used and generated by research activities are well-described, documented, findable, retrievable, understandable, and preserved for some period of time.

Why should I be interested in this?

Effective data management results in no lost or corrupted data, easier identification and handling of data during projects and after, and more time for research activities. In addition, increasingly external funders require data management (and sharing) plans so that funded research can serve as foundations for future research and previous investments can continue to yield dividends.  

 

      
     

    Data Life Cycle Models

    There are many ways to visualize the life cycle of data.  Here are three prominent models: 

    DataOne Data Life Cycle

    Data Life Cycle-Plan, Collect, Assure, Describe, Preserve, Discover, Integrate, Analyse

    MIT Data Management Cycle

    Data Management Cycle-Study Concept, Data Collection, Data Processing | Data Archiving, Data Discovery, Data Analysis, Repurposing

    Rutgers University Community Repository Data Life Cycle

    Rutgers University Data Life Cycle

    Tools Shortcuts

    • DMPTool  
        
      Use this tool for guided creation of data management plans.
    • TideShare  
        
      After setting up a TideShare account with OIT, use this tool for managing and sharing in-process data, documents, schedules, and communication.
    • Dataverse Network  
        
      Use this tool to store, describe, version, preserve, and share data and documents.
    • UA Box  
        
      UA Box provides a secure, managed, cloud-based toolset and storage to facilitate collaboration and anywhere-access to active files and data. All data is encrypted both in transit and storage and is maintained on domestic servers.
     

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