A Bottom-up Approach to Data Annotation in Neurophysiology - Grewe, Jan; Wachtler, Thomas; Benda, Jan (Frontiers in Neuroinformatics, 2011)
Metadata providing information about the stimulus, data acquisition, and experimental conditions are indispensable for the analysis and management of experimental data within a lab. However, only rarely are metadata available in a structured, comprehensive, and machine-readable form. This poses a severe problem for ﬁnding and retrieving data, both in the laboratory and on the various emerging public data bases. Here, we propose a simple format, the ”Open metaData Markup Language” (od ML), for collecting and exchanging metadata in an automated, computer-based fashion. In od ML arbitrary metadata informa- tion is stored as extended key-value pairs in a hierarchical structure. Central to od ML is a clear separation of format and content, i.e. neither keys nor values are deﬁned by the format. This makes od ML ﬂexible enough for storing all available metadata instantly with- out the necessity to submit new keys to an ontology or controlled terminology. Common standard keys can be deﬁned in od ML terminologies for guaranteeing interoperability. We started to deﬁne such terminologies for neurophysiological data, but aim at a community driven extension and reﬁnement of the proposed deﬁnitions. By customized terminologies that map to these standard terminologies, metadata can be named and organized as required or preferred without softening the standard. Together with the respective libraries provided for common programming languages, the od ML format can be integrated into the labora- tory workﬂow, facilitating automated collection of metadata information where it becomes available. The ﬂexibility of od ML also encourages a community driven collection and deﬁnition of terms used for annotating data in the neurosciences.