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{{Paper
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|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2849/paper-27.pdf
|volume=Vol-2849
|dblpUrl=https://dblp.org/rec/conf/swat4ls/HammerRFHGS19
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==None==
https://ceur-ws.org/Vol-2849/paper-27.pdf
The 4DN-OME ontology: an OME-OWL extension with
emphasis on usability, minimum information guidelines
and quality control for super-resolution fluorescence
microscopy
Mathias Hammer1,3, Alex Rigano2, Farzin Farzam1, Maximiliaan Huisman1, David
Grunwald1, and Caterina Strambio de Castillia2
1
RNA Therapeutics Institute and 2 Program in Molecular Medicine University of Massachu-
setts Medical School, Worcester, MA, USA; 3 Department of Biology, TU Darmstadt, Germany
{david.grunwald, caterina.strambio}@umassmed.edu
Abstract. The Open Microscopy Environment (OME) model [1] is a specifica-
tion for sharing biological imaging data that stores metadata as OME-XML. The
OME Consortium recently introduced the OME core-ontology [2, 3] as a basis to
facilitate the introduction of domain-specific metadata extensions. The 4D Nu-
cleome [4] is an NIH initiative that funds ~600 researchers in ~50 independent
laboratories. A central aim is to map the localization of single genomic loci ob-
tained by fluorescence microscopy onto global chromatin topology maps ob-
tained by Chromatin Conformation Capture (CCC) experiments. As part of this
effort, the 4DN Imaging Data Working Group (IWG) is proposing the 4DN-OME
ontology, an extension of the OME-core ontology, specifically tailored at en-
hancing the reproducibility and comparison of single-molecule, super-resolution
fluorescence microscopy experiments. To reduce the record-keeping burden im-
posed by the proposed guidelines, the interactive Micro-Meta App was developed
to guides experimental biologists through the workflow required to document
tier-dependent hardware specifications. This poster presents the proposed 4DN-
OME ontology and reports on the status of underlying application development.
Keywords: Open Microscopy Environment, 4D Nucleome, super-resolu-
tion microscopy, imaging ontology, data provenance, quality control
1 Introduction
Because the information content of image data is not machine-readable, microscopy
images need to be accompanied by thorough documentation of the microscope hard-
ware and imaging settings to ensure a correct interpretation of the results. A significant
challenge with the reproducibility of microscopy results and with their integration with
chromatin folding maps generated by the 4DN consortium lies in the lack of shared
super-resolution microscopy reporting guidelines and of instrument performance and
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
2
calibration standards. The proposed 4DN-OME ontology is put forth as an extension of
the OME core-ontology to help address this challenge.
2 The 4DN-OME ontology
The 4DN-OME ontology is being developed on the basis of the proposed 4DN exten-
sion [5] of the OME xml model. This proposed ontology has the following key features:
1) a tiered-system of reporting guidelines that scales required metadata content with
experimental complexity. 2) A metadata model designed to better capture the technical
complexity of high-resolution single-molecule localization and single-particle tracking
experiments. 3) The introduction of standards for fluorescence microscope calibration
and quantitative instrument performance assessment. In addition to introducing the con-
cept of graded documentation requirements based on a tiered-system of guidelines, the
4DN-OME proposal extends the existing the OME core-classes `Instrument’ and
`Image’ to reflect the technological advances and the quality control requirements
associated with single-molecule, super-resolution microscopy. To this aim, the pro-
posal put forth several types of modifications. First, additional classes and attributes
were introduced to capture the complexity of microscope hardware commonly encoun-
tered in the field and their calibration requirements. Second, abstract concepts were
proposed to describe hardware components that commonly require specialization (i.e.,
‘Detector’). Finally, the concept of individual ‘WavelengthRange’ class was
established to facilitate the description of multi-pass filters, and dichroic-mirrors.
3 Development of Micro-Meta App
Micro-Meta App [6] provides an interactive future-proof approach to document imag-
ing experiments based on the 4DN-OME ontology and the proposed tiered-system of
guidelines. The user’s data processing workflow consists of the following steps: 1) The
App helps users build graphical representations of the microscope hardware by drag-
ging-and-dropping individual components onto the workspace and entering the relevant
attribute values based on the desired tier level. 2) Micro-Meta App builds tier-specific
instances of `Instrument’ class containing structured descriptions of the microscope
hardware and outputs them as interoperable JSON files that can be shared with the
community. 3) Finally, Micro-Meta App consumes these JSON documents, collects
instrument-specific and tier-appropriate image acquisition settings, and stores them in
the instances of `Image’ class. The resulting documentation of individual microscopy
datasets can be stored on the user’s file system or consumed by third-party data portals.
References
1. Goldberg IG, et al. Genome Biol, 6, R47, (2005).
2. Kobayashi N, et al. SWAT4HCLS 2019, Paper 29 (2019).
3. Moore J, et al. SWAT4HCLS 2019, Paper 17 (2019).
4. Dekker J, et al. Nature, 549:219–26 (2017).
5. Huisman M, et al. arXiv:1910.11370 [q-bio.QM] (2019).
6. https://github.com/WU-BIMAC/4DNMicroscopyMetadataTool