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Quality

HathiTrust commitment to quality

  • In all cases, HathiTrust materials are subject to quality review as a fundamental step in the digitization process.  Materials digitized by partners institutions or those made available through entities such as the Internet Archive are subject to formal quality review processes prior to the digital content entering the HathiTrust.
  • In the case of materials digitized by Google, HathiTrust devotes significant resources to ensuring the highest possible quality content, despite the extraordinarily high volume of material. This work is in addition to the substantial quality assurance processes Google undertakes.
  • Google provides automated quality metrics which HathiTrust uses to create thresholds for what enters the repository.  
  • Individual partners commit resources to externally verifying the quality of the materials, and document systemic problems in the digitization process.  For example, Michigan has devoted significant staff resources to collecting longitudinal data on quality, which has in turn influenced both the digitization and post-processing work of Google.
  • Partners work with Google to address specific quality issues and problems raised by the user community.
  • HathiTrust partners that collaborate with Google have worked collectively to refine quality indicators and even processes.
  • Overall, in HathiTrust, partners have devoted attention to giving better definition to a shared sense of quality, beginning with a pilot effort (with support from the Mellon Foundation), which is now evolving into a large-scale community effort funded by IMLS.  Through this initiative, we hope to develop shared definitions of quality which will, in turn, further our ability to certify objects for specific intended purposes.
  • HathiTrust’s processes rely on partner-contributed descriptive cataloging, ensuring that discovery is based on the highest standards of bibliographic data. HathiTrust does not rely on automated approaches to gather information about the works or infer information about the identity of the work from the metadata.