Metadata management for high content screening in OMERO

Methods. 2016 Mar 1:96:27-32. doi: 10.1016/j.ymeth.2015.10.006. Epub 2015 Oct 22.


High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at

Keywords: Data management; HCS; Metadata; Screening.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Computational Biology / statistics & numerical data*
  • Data Mining / statistics & numerical data*
  • Datasets as Topic
  • High-Throughput Screening Assays / methods
  • High-Throughput Screening Assays / statistics & numerical data*
  • Humans
  • Information Dissemination
  • Information Storage and Retrieval / methods
  • Information Storage and Retrieval / statistics & numerical data*
  • Internet
  • Software*