OHSU Informatics Analytics BD2K Skill Course
OHSU Informatics Analytics BD2K Skill Course
批准号:
9063158
负责人:
DAVID A. DORR
金额:
$16.2万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-29 至 2017-10-31
关键词:
AddressBig DataBig Data to KnowledgeBioinformaticsCase StudyClinical DataCompetenceComplexComputational BiologyDataData AnalysesData AnalyticsData ScienceData SetEducationElementsEnvironmentExerciseFutureGoalsGrantHealthHybridsInformaticsInformation RetrievalInstitutionInstructionKnowledgeMelissaMentorsMetadataMethodologyMethodsNeeds AssessmentOntologyParticipantPersonsPreparationProblem SetsPublic HealthRecruitment ActivityReproducibilityResearchResearch PersonnelResourcesScienceSecureSeminalSeriesSignal TransductionStagingStructureStudentsSystemTeaching MethodTechniquesTestingTimeTrainingUnited States National Institutes of HealthWorkcareerdata wranglingeducational atmosphereexperiencegraduate studentimprovedonline coursepopulation healthprecision medicinerepositoryskillsstudent trainingweb page
中文摘要
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英文摘要
DESCRIPTION: We propose to create and disseminate an OHSU Informatics Analytics BD2K Skill Course to enable researchers and students at any career stage to gain crucial analytics and data skills and competencies as part of the Big Data to Knowledge (BD2K) initiative. Although the potential of big data to advance research is enormous, our needs assessment has identified that a wide range of researchers and graduate students lack fundamental skills in identifying the appropriate data sets to answer their hypotheses, in managing and 'wrangling' data to prepare it for analysis, and in using both common and advanced methods to analyze the data. These needs varied by experience and skill of the researcher. We therefore propose three educational components: the first is to recruit a diverse set of participants and work to inculcate
a fundamental set of competencies in basic big data skills; the second is to create realistic but synthetic large datasets with embedded signals where students can practice their skills in collaborative and interactive exercises; the third is to create advanced challenges to help researchers test and implement more advanced methodologies. We anticipate the impact to be substantial in enabling researchers to improve their use of big data to more rapidly and accurately address important research hypotheses. We will disseminate this work via online curricula resources and public venues and share the datasets created so that others may train their own teams.
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会议论文
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财政年份:2008
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依托单位:
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: