The following outlines specific scenarios involving BrainML in
support of interchange and interoperability within or between
The simplest use of BrainML is a single neuroscience data repository
providing a web interface. The server uses BrainML as an
intermediate stage when providing query results, and accepts data
submissions in BrainML format. The advantages gained from using
BrainML as opposed to an ordinary XML or a non-XML format are based
on the use of XML Schema and the systematicity of BrainML in which
different data models are expressed using the same underlying
Submissions can be checked for consistency / completeness using
standard XML Schema validation software, independently of what
BrainML model is used.
Query results can be formatted for simple display independently
of the BrainML model used.
Most of the processing of BrainML can be handled in a generic
way, based on BrainML itself, rather than the specific model
used. This allows the data model to evolve with only minor
changes to the hosting software required. BrainML provides a
versioning mechanism so that software can easily determine
whether it is compatible with a given data document.
BrainML is an open, self-documenting format, so it is easy for
third parties to write software for interfacing to the repository.
Generic Data Handling Capabilities
In neuroscience, the diversity of preparations and experimental
methods exceeds the diversity of data types collected. Thus we
expect that aspects of data models for describing things like
recording sites and recording technique will vary between
communities while aspects for describing the actual data values
(time series, image array, etc.) often remain constant. BrainML is
designed to allow reuse of model components for such common elements
when creating new data models without compromising the ability to
represent new specialized forms of data. This can potentially allow
client client tools designed to work with the common components to
work with a variety of data models.
The "virtual oscilloscope" module built into the query tool at
capable of reading the BrainML base data container format,
including structures for a variety of time series traces,
histograms, and X-Y plots. It is expected this data container
format will be shared by many data models independently of their
other characteristics, all of which the viewer module will be able
A tool being developed by Bruxton
Corporation will also operate on the data container
format, but functioning to transfer the data to analysis programs
such as MATLAB and SigmaPlot.
Finally, the Laboratory of Neuroinformatics is developing a
library of diverse analytical routines under a common interface
to operate on neurophysiology data. An tool will be built to
load BrainML data container data to be processed by this
The ability of BrainML models to share common components can support
some forms of integration across neuroscience data repositories.
For example, a single client interface can initiate a search across
multiple repositories based on common components, such as authors,
data types, recording sites, or techniques. The search may return
back results from different data models, however the client
interface can still parse the responses based on the basic BrainML
format and conventions, and organize the results according to the
components it does understand. In addition, utilization of the
raw data may be aided if the BrainML data container format is used
for all the data sets.
If a collection of neuroscience repositories all provide BrainML
interfaces, this shared basic structure can be used to catalog the
repositories in a single index, searchable by content. This would
support the creation of meta-resources like the SFN Neuroscience Database
Gateway and the in-development Neuroscience Information