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DTSTAMP:20260711T163303Z
UID:e49370e7-da56-4463-8b54-8a1a951740a5
DTSTART:20221209T120000Z
DTEND:20221209T150000Z
DESCRIPTION:Life science researchers often need to extract\, manipulate and
  integrate data and/or metadata from different sources\, such as repositor
 ies\, databases or flat files. Much research time is spent on trivial and 
 not-so-trivial details of data wrangling: to reformat data structures\; cl
 ean up errors\; remove duplicate data\; or map and integrate dataset field
 s. Software for data wrangling and analysis\, such as Pandas\, R or Fricti
 onless\, is useful\, but researchers still regularly end up with hard-to-r
 euse scripts\, often with manual steps. uniFAIR is a new Python library wi
 th a systematic and scalable approach to research data wrangling. With uni
 FAIR\, researchers can import (meta)data in almost any shape or form: nest
 ed JSON\; tabular (relational) data\; binary streams\; or other data struc
 tures. Data is continuously parsed and reshaped through a step-by-step pro
 cess according to a series of data model transformations. uniFAIR provides
  a catalogue of generic task and subflow templates that the researcher can
  refine and apply to carry out the transformations needed to wrangle data 
 into the required shape. For large datasets\, uniFAIR allows local test jo
 bs on sample-sized data to be seamlessly scaled up to the full datasets an
 d offloaded to external compute resources. Persistent access to the state 
 of the data is available at every step. This workshop will introduce you t
 o the technical and conceptual background needed to make use of uniFAIR\, 
 including the new type hints in Python. Participants will follow hands-on 
 tutorials that are based on a series of use cases from genomics\, proteomi
 cs\, and machine learning.
LOCATION:Ole-Johan Dahl's House\, 23B Gaustadalléen
SUMMARY:Hands-on introduction to uniFAIR: a systematic and scalable approac
 h to research data wrangling in Python
URL;VALUE=URI:https://www.mn.uio.no/sbi/english/events/oslo-bioinformatics-
 week-2022/#19
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