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| Big Data to Knowledge | |
|---|---|
| Name | Big Data to Knowledge |
| Field | Data science |
| Introduced | 2009 |
| Key people | Barack Obama, Francis Collins, Vinton Cerf, John Holdren, Neelie Kroes |
| Institutions | National Institutes of Health, National Science Foundation, European Commission, DARPA, Wellcome Trust |
| Related concepts | Human Genome Project, Hubble Space Telescope, Large Hadron Collider, Square Kilometre Array |
Big Data to Knowledge
Big Data to Knowledge is an interdisciplinary initiative and practice that transforms large-scale datasets into actionable scientific and operational insights. It brings together actors from National Institutes of Health, National Science Foundation, European Commission, DARPA, and philanthropic bodies like the Wellcome Trust to accelerate discovery across projects such as the Human Genome Project, the Large Hadron Collider, and the Square Kilometre Array. The effort interfaces with policy leaders including Barack Obama, scientific administrators like Francis Collins, and technologists such as Vinton Cerf and John Holdren, while influencing regulatory agendas of figures like Neelie Kroes.
This programmatic area spans activities in agencies such as National Institutes of Health, National Science Foundation, European Commission, Defense Advanced Research Projects Agency (DARPA), and partnerships with institutions like the Wellcome Trust, the World Health Organization, and the European Research Council. It encompasses integration of datasets from projects including the Human Genome Project, the Hubble Space Telescope, the Large Hadron Collider, and the Square Kilometre Array, and supports missions led by agencies such as NASA, ESA, and NOAA. Prominent stakeholders include policymakers (Barack Obama, John Holdren), scientific leaders (Francis Collins, Harold Varmus), and industry figures (Vinton Cerf, Tim Berners-Lee).
Data acquisition often involves collaborations among research centres like Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, CERN, and Argonne National Laboratory, as well as private firms like Google, Amazon (company), Microsoft, IBM, and Facebook. Standards and infrastructures draw on initiatives from Internet Engineering Task Force, World Wide Web Consortium, Open Data Institute, and regulatory frameworks influenced by entities such as the European Commission and national bodies including the National Institutes of Health. Large repositories and computing platforms include Amazon Web Services, Google Cloud Platform, Microsoft Azure, XSEDE, and facilities at Oak Ridge National Laboratory. Data stewardship practices are informed by precedents from the Human Genome Project and archives like the Smithsonian Institution and Library of Congress.
Advanced analytics employ methods developed in academic centres such as Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Carnegie Mellon University, and University of Oxford, and leverage software ecosystems originating from projects like Apache Hadoop, Apache Spark, TensorFlow, and PyTorch. Research collaborations span laboratories including Sandia National Laboratories and companies such as NVIDIA and Intel Corporation. Computational models are validated against datasets produced by experiments at Large Hadron Collider experiments like ATLAS experiment and CMS experiment, remote sensing from Landsat program and Copernicus Programme, and clinical trials administered through National Institutes of Health networks.
Ontologies, vocabularies, and semantic frameworks draw on efforts by Gene Ontology Consortium, Open Biological and Biomedical Ontology, W3C, and databases such as GenBank, European Nucleotide Archive, and Protein Data Bank. Integration aligns with standards from ClinicalTrials.gov, FAST Healthcare Interoperability Resources, and archives like the PubMed Central and arXiv. Cross-domain projects involve collaborations with institutions such as European Molecular Biology Laboratory and initiatives like the Human Cell Atlas and ENCODE Project, while governance discussions engage bodies including World Health Organization and International Monetary Fund on implications for global research infrastructures.
Applications span healthcare, astronomy, particle physics, climate science, and urban planning with deployments in hospitals like Mayo Clinic and research sites such as CERN and JPL. Clinical genomics projects at Broad Institute and Sanger Institute translate sequence data into therapeutics; environmental monitoring uses data from NOAA and European Space Agency missions; smart-city efforts integrate datasets from municipal partners including City of New York and Singapore agencies. Industry adoption appears in platforms from IBM Watson, Google DeepMind, Amazon Web Services, and Palantir Technologies, supporting enterprises like Pfizer, Roche, Siemens, and General Electric.
Policy, ethics, and law debates engage actors such as European Commission, United States Department of Health and Human Services, European Court of Human Rights, and advocacy groups including Electronic Frontier Foundation and Privacy International. High-profile incidents involving Cambridge Analytica influenced regulation and oversight discussions in legislatures like the United States Congress and institutions such as the European Parliament. Consent frameworks, data protection regimes, and patient privacy policies reference statutes like data protection regimes shaped by member states of the European Union and national agencies such as Office for Civil Rights (OCR). Ethical guidance is advanced by committees at National Academies of Sciences, Engineering, and Medicine and organizations like the World Medical Association.
Key technical and institutional challenges require collaboration among universities (e.g., Harvard University, Yale University), national laboratories (Lawrence Livermore National Laboratory), and corporations (Google, Microsoft, Amazon (company)). Future directions include scalable architectures inspired by Exascale Computing Project, federated learning practices promoted by research groups at Stanford University and MIT, and reproducibility initiatives echoing the practices of Nature (journal) and Science (journal). International coordination will involve multilateral institutions like the United Nations and funding agencies including Wellcome Trust and Gates Foundation to ensure equitable access, while standards development will continue at bodies like the W3C and IEEE.
Category:Data science