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So far the Pandora project is still under heavy development and should not be seen as a final product. However, the models as well as the HDF5 schema definition are already quite advanced and can be considered more or less stable. (more)
The Pandora project started as an initiative of the electrophysiology Task Force which is part of the INCF Datasharing Program. As such the project aims to develop standardized methods and models for storing electrophysiology and other neuroscience data together with their metadata in one common file format based on HDF5.
In order to achieve this, Pandora uses highly generic models for data as well as for metadata and defines standard schamata for HDF5 files which can represent those models. Last but not least Pandora aims to provide a convenient C++ library to simplify the access to the defined format. (more)
The design principle of the data model used by Pandora, was to create a rather minimalistic, generic, yet expressive model, that is able to represent data stored in other widely used formats or models like Neuroshare or NEO without any loss of information. Due to its generic approach, the data model is furthermore able to represent also other kinds of data used in the fieldlike image data or image stacks.
Since Pandora was also designed to annotate data with metadata the model also includes the odML model for metadata which was published by Jan Grewe et al. (2011).
Neither the model for data nor the model for metadata (odML) are domain specific to electrophysiology, but both models can be linked to predefined or custom terminologies which enables the user to give elements of the models a domain specific, semantic context. (more)
Based on the Pandora data model we develop a schema for HDF5 files.
Read more about the HDF5 schema
Due to its generic character of the Pandora data model, there is not one single way of representing certain kinds of electrophysiological data e.g. analog signals, neural events or spike trains. We therefore provide some guidelines that describe how to represent electrophysiological data using the Pandora model.
