Data processing


Data processing is a set of methods that are used to input, retrieve, verify, store, organize, analyse or interpret a set of data. Data processing enables information to be automatically extracted from data, and could be used in computational biology and bioinformatics to organise a large set of 'omics data.

Latest Research and Reviews

News and Comment

  • Editorial |

    This journal and Scientific Data are calling for submissions containing linked open data models that embody and extend the FAIR principles: that data should be findable, accessible, interoperable and reusable by both humans and machines. These principles are achievable with existing resources, languages and vocabularies to enable computers to combine and reanalyze data sets automatically and lead humans to new discoveries.

  • Comments and Opinion |

    • John Vivian
    • , Arjun Arkal Rao
    • , Frank Austin Nothaft
    • , Christopher Ketchum
    • , Joel Armstrong
    • , Adam Novak
    • , Jacob Pfeil
    • , Jake Narkizian
    • , Alden D Deran
    • , Audrey Musselman-Brown
    • , Hannes Schmidt
    • , Peter Amstutz
    • , Brian Craft
    • , Mary Goldman
    • , Kate Rosenbloom
    • , Melissa Cline
    • , Brian O'Connor
    • , Megan Hanna
    • , Chet Birger
    • , W James Kent
    • , David A Patterson
    • , Anthony D Joseph
    • , Jingchun Zhu
    • , Sasha Zaranek
    • , Gad Getz
    • , David Haussler
    •  & Benedict Paten
    Nature Biotechnology 35, 314–316
  • Comments and Opinion |

    The way in which data on conflict violence is collected can not only lead to severe underestimation of the human toll of conflict, but also to misinterpretation of trends in conflict violence, says Megan Price.

    • Megan Price
  • Editorial |

    A prevalent but trivial systematic error in supplementary tables provides a reminder that genomic and other large data files are most usable when they are readable by both humans and machines. It is best practice to deposit large files in public databases and to provide accession links for peer review rather than to delay data deposition until publication.

  • Editorial |

    A recent recommendation that a large number of professional data stewards be trained and employed in all data-rich research projects raises the exciting prospect they will conduct research on data-intensive research itself. It also focuses us on questions about the role of all scientists in data quality and accessibility as well as how best to measure the value of good data stewardship to science and society.