Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators
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{"title"=>"Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators", "type"=>"journal", "authors"=>[{"first_name"=>"Lindsay", "last_name"=>"Barone", "scopus_author_id"=>"57196260303"}, {"first_name"=>"Jason", "last_name"=>"Williams", "scopus_author_id"=>"56310215300"}, {"first_name"=>"David", "last_name"=>"Micklos", "scopus_author_id"=>"6507371056"}], "year"=>2017, "source"=>"PLoS Computational Biology", "identifiers"=>{"issn"=>"15537358", "doi"=>"10.1371/journal.pcbi.1005755", "sgr"=>"85032435239", "scopus"=>"2-s2.0-85032435239", "isbn"=>"1111111111", "pmid"=>"29049281", "pui"=>"619081502"}, "id"=>"bff3fd72-8e63-3b6c-8cfe-6509e285d290", "abstract"=>"In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.", "link"=>"http://www.mendeley.com/research/unmet-needs-analyzing-biological-big-data-survey-704-nsf-principal-investigators", "reader_count"=>78, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>13, "Librarian"=>4, "Researcher"=>29, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>13, "Other"=>3, "Student > Master"=>3, "Lecturer"=>3, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>13, "Librarian"=>4, "Researcher"=>29, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>13, "Other"=>3, "Student > Master"=>3, "Lecturer"=>3, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Agricultural and Biological Sciences"=>31, "Chemistry"=>3, "Computer Science"=>10, "Earth and Planetary Sciences"=>1, "Engineering"=>3, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>14, "Mathematics"=>1, "Medicine and Dentistry"=>1, "Neuroscience"=>3, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Engineering"=>{"Engineering"=>3}, "Chemistry"=>{"Chemistry"=>3}, "Neuroscience"=>{"Neuroscience"=>3}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>31}, "Computer Science"=>{"Computer Science"=>10}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>14}}, "reader_count_by_country"=>{"Norway"=>1, "United States"=>2, "Germany"=>1}, "group_count"=>11}

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