Event Abstract

Describing neurophysiology data and metadata with OEN, the Ontology for Experimental Neurophysiology

  • 1 Ludwig-Maximilians-Universität München, Department Biology II, Germany
  • 2 University of Antwerp, Belgium
  • 3 The University of California, San Diego, Neuroscience Information Framework, Center for Research in Biological Systems, United States
  • 4 University of West Bohemia, Dept. of Computer Science and Engineering, Czechia
  • 5 University of West Bohemia, New Technologies for Information Society,, Czechia
  • 6 Eberhard Karls University Tübingen, Germany
  • 7 University of British Columbia, Ctr. for High Throughput Biology and Dept. of Psychiatry, Canada

One of the major issues in Neurophysiology is the large diversity of data formats used to store both raw data and the associated metadata. The INCF Program on Standards for Data Sharing with the Task Force on electrophysiology (incf.org/programs/datasharing/electrophysiology-task-force) is concerned with developing data formats and metadata standards to alleviate this situation. However, existing ontological resources continue to lack terms for accurately and unambiguously annotating the breadth of electrophysiological data. With the development of different resources for sharing this particular type of data, the community needs controlled vocabularies to standardize the descriptions of the different types of recording paradigms, parameters and experimental procedures. Thus we have started developing the Ontology for Experimental Neurophysiology (OEN, https://github.com/G-Node/OEN). Because electrophysiology as a field is heterogeneous and the corresponding scope of the ontology considerable, the development of the OEN has been separated along two main branches: a branch considering devices and methods, and a branch considering neurophysiological concepts. Building a terminology describing neurophysiological concepts (e.g. action potential, synaptic plasticity, afterhyperpolarisation potential,…) is difficult as these concepts legitimately belong to more than one ontology branch. This ontological entailments, i.e., what is allowed as a property of the term, will be different depending on the ontology branch increasing the complexity of the knowledge model. To address this difficulty we have devised a strategy using web-based surveys and detailed literature analyses to study how these terms are used by the community while ensuring that they are immediately usable in affiliated projects by importing terms related to Neurophysiological concepts into NeuroLex (neurolex.org). The development of the device/method branch is use-case driven with the first aims of precisely describing specific lab devices and methods, annotating the EEGbase database (http://eegdatabase.kiv.zcu.cz/), and enriching odML descriptions (www.g-node.org/odml/terminologies) with structured semantic information. In order to maximize the interoperability of the OEN device/method branch, terms for electrophysiological methods, tools and parameters gathered from various sources (EEGBase, odML terminologies, Neurolex,…) are mapped with existing ontologies related to experiments or investigation, including OBI (obi-ontology.org), NEMO (purl.bioontology.org/ontology/NEMO) and ERO (https://code.google.com/p/eagle-i/wiki/Documentation), The terms already defined in these ontologies are incorporated in OEN using the MIREOT approach (Courtot et al., 2011). The various terms composing the OEN device/method branch are contained in a dedicated terminology which will be used to build formal models describing necessary complex concepts such as experiment setups, acquisition system settings, workflows, etc. Thus, the OEN is a comprehensive basis to build common knowledge models to enrich existing neurophysiological resources.

Acknowledgements

Supported by the German INCF Node (BMBF grant 01GQ1302) and the European Regional Development Fund (ERDF), Project "NTIS - New Technologies for Information Society", European Centre of Excellence, CZ.1.05/1.1.00/02.0090.

References

Courtot M., Gibson F., Lister A.L., Malone J., Schober D., Brinkman R.R., Ruttenberg A., MIREOT: The minimum information to reference an external ontology term, 2011, J. Appl. Ontol., 6(1):23-33

Keywords: ontology, Neurophysiology, metadata, annotation, OWL

Conference: Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014.

Presentation Type: Poster, not to be considered for oral presentation

Topic: Electrophysiology

Citation: Le Franc Y, Bandrowski A, Brůha P, Papež V, Grewe J, Mouček R, Tripathy SJ and Wachtler T (2014). Describing neurophysiology data and metadata with OEN, the Ontology for Experimental Neurophysiology. Front. Neuroinform. Conference Abstract: Neuroinformatics 2014. doi: 10.3389/conf.fninf.2014.18.00044

Received: 26 Apr 2014; Published Online: 04 Jun 2014.

* Correspondence: Dr. Yann Le Franc, Ludwig-Maximilians-Universität München, Department Biology II, Planegg-Martinsried, Germany, ylefranc@gmail.com

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