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Managing the research life cycle

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Managing the Research Life Cycle

Managing the Research Data Life CyclePresented by Sherry [email protected] 31, 2012 University of Florida Data Management Workshop

This class is aimed at those engaged in the life cycle of research, from applying for research grant, thru data collection & ultimately to preparation of the data for deposit in a public archive.

Some projects generate enormous amounts of data that it takes up much of the scientists time. Data management primarily occurs within the lifecycle of a research porject.

Data sharing plans should be developed in conjunction with an archive to maximize the utility of the data to research and to ensure the availability of the data in the future. 1Research Life CycleData Life CycleRe-PurposeRe-UseDepositDataCollectionDataAnalysisDataSharingProposal Planning WritingData DiscoveryEnd of ProjectDataArchiveProjectStart Up

Steps in the Research Life Cycle:Proposal Planning & Writing: Conduct a review of existing data setsDetermine if project will produce a new dataset (or combing existing)Investigate archiving challenges, consent and confidentialityId potential users of your dataDetermine costs related to archivingContact Archives for advice (Look for archives)Project Start Up Create a data management planMake decisions about document form and contentConduct pretest & tests of materials and methodsData CollectionFollow Best PracticeOrganize files, backups & storage, QA for data collectionAccess Control and SecurityData Analysis Manage file versionsDocument analysis and file manipulationsData Sharing Determine file formatsContact Archive for adviceMore documenting and cleaning up dataEnd of Project Write PaperSubmit Report FindingsDeposit Data in Data Archive (Repository)Remember: Managing Data in a research project is a process that runs throughout the project. Good data management is the foundation for good research. Especially if you are going to share your data. Good management is essential to ensure that data can be preserved and remain accessible I the long-term, so it can be re-used and understood by other researchers. When managed and preserved properly research data can be successfully used for future scientific purposes.

2Why Manage Data?Saves timeOthers can understand your dataMakes sharing/preserving data easierReinforces open scientific inquiry and replication of resultsIncreases the visibility of your researchFacilitates new discoveriesReduces costs by avoiding duplicationRequired by funding agencies

Proposal Planning WritingPlanning the management of your data before you begin your research AND throughout its lifecycle is essential to ensure its current usability & long-term preservation and access.

Can focus on research not user requestsWith a repository keeping your data, you can focus on your research rather than fielding requests or worrying about data on a web page. Your project may have lots of people working on it, you will need to know what each is doing and has done. Project may last years.

Funding agencies now require a data management plan

You can understand your data at a later timeHaving your data documented will allow future users understand your data and be able to use it.

Takes less time to get data ready to shareIf follow plan then data should be ready for archiving (documenting the data throughout) insures proper description of the data are maintained.

3Ethical and Legal IssuesConfidentialityEvaluate the sensitivity of your dataComply with institutions research guidelinesComply with regulations for health researchMay need to enable a restricted view of your dataIntellectual PropertyCopyrightPatents

Proposal Planning WritingWill the data contain direct or indirect identifiers that could be used to identify research participants?

Challenges for archiving data. Need to think about consent

Links on Uva compliance in research links on handout.Health Research links on handouts too. HIPPA Privacy Rule (Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule is the first comprehensive Federal protection for the privacy of personal health information)

Your discipline may have other policies, i.e. National Academy of Engineering (link on handouts)

Intellectual Property-determine copyright & ownership of research dataIf youve gathered the data from multiple sources, need to obtain permission to publish it.

4Data Sharing and Retention RequirementsBe Aware of Funding RequirementsInformal sharing statementSeparate Data Management Plan Know What Your Institution RequiresKnow What Your Department RequiresPublishers RequirementNature Magazine

Proposal Planning WritingRegarding research data generated from proposal/project Sharing and Data RetentionBefore you start your plan check mandates, policies, & procedures of grant funding and UvaExample from UVA: UVas policy on recordkeeping in research, Uvas Health System Office of Research

NIH Data Sharing Policy & Implementation Guidance (2003) suggests the following in the proposals: Schedule for data sharing Format of final dataset Documentation to be provided Analytical tools to be provided, if any Need for data sharing agreement Mode of data sharing

NIH generally requires that files resulting from research awards be retained for at least three years after the final financial report has been filed. However, Commonwealth of Virginia record retention regulations are more strict (see below) and require that such records be retained five years after filing of the final financial report of a funding period

NSFdevelop and submit specific plans to share materials collected with NSF support, except where this is inappropriate or impossible. These plans should cover how and where these materials will be stored at reasonable cost, and how access will be provided to other researchers, generally at their cost.

UVaData and notebooks resulting from sponsored research are the property of the University of Virginia. It is the responsibility of the principal investigator to retain all raw data in laboratory notebooks (or other appropriate format) for at least five years after completion of the research project (i.e., publication of a paper describing the work, or termination of the supporting research grant, whichever comes first) unless required to be retained longer by contract, law, regulation, or by some reasonable continuing need to refer to them.

Uva Health SystemHas a responsible conduct of research that includes data management (protection, sharing, retention times)5Create a Data Management PlanAppoint Data Manager ContactDescribe data to be collected and methodologyInclude guidelines on data documentationPlan quality assurance and backup proceduresPlan sharing of data for public useInclude preservation plansDocument copyright and intellectual property rightsProjectStart Up

How do you get started managing data.

So how do I get started managing data?

Handout has a link to Managing & Sharing Data with more detailsAlso link to a Data Management Plan Form

Should be written down sort like an instruction book.6Data Life Cyclewithin Context of the Research Life CycleData Life CycleRe-PurposeDataCollectionDataAnalysisDataSharingRe-UseDepositProposal Planning WritingData DiscoveryEnd of ProjectDataArchiveProject Start Up

Life cycle of a research project with respect to the data it creates:Data Collectiondata collection, entry, checking & cleaningData Analysisanalyze data, derived new data, data documentationData Sharingprepare data for submission

Managing the Data in the Data Life Cycleincludes: backup & storage, version control, file conversions, security & access controlDocument all data details 7Managing Data in the Data Life CycleData Collection and OrganizationData Control & SecurityBackup & StorageDocumentation and MetadataProcessing and AnalysisPreparing Data to Share

Heres the details about what we are going to manage in the Data Life Cycle.

8What is Data?Observational data captured in real-timeExamples: Sensor readings, telemetry, survey results, imagesUsually irreplaceable

Experimental data from lab equipmentExamples: gene sequences, chromatograms, magnetic field readingsOften reproducible, but can be expensive

National Science Board. (2005). Long-lived digital data collections: Enabling research and education in the 21st century. Retrieved from http://www.nsf.gov/pubs/2005/nsb0540/nsb0540.pdf

observational data cannot be recollected and are archived indefinitely. cannot be recollected, remeasured, or verified. Data are typi- cally time and/or location dependent. This context is set by the fact that much of the value of observational data is in its secondary analysis.

Experimental data can often be reproduced, although there are cases where experimental conditions or variables are unknown. Experimental data may be associated with a particular meth- odology or instrument

9What is Data?Simulation data generated from test modelsExamples: climate models, economic modelsModels & metadata (inputs) more important than output data

Derived or compiled dataExamples: text and data mining, compiled database, 3D modelsReproducible (but very expensive)

These are sometimes lumped together as computational data:Data that is the result of computer models or simulations can be reproduced if adequate infor- mation is provided about the computer hardware, software, and inputs.

Statistical data, computational models, and simulations can also be recreated and verified, as long as sufficient disciplines

Can you think of anything else as data?

Most of the time we are managing the digital data, wh

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