They may capture data using different instruments, different databases, different data architectures, different data elements and immensely different formats.
Lack of standards, unstructured data formats and aggregation of data (elements and cases) inhibit the semantic content processing, search and holistic data understanding.
Text-only format provides less than optimal for entry of selected data elements and presentation on reports, and many obstacles to data retrieval by distinct data elements as audited in a project in early 2004.
Starting from 2002, the Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) has made an effort to develop molecular interaction data standards, data interchange formats and controlled vocabularies with which to implement these standards in a consistent manner (5, 6).
The PSI-MI standard is only one of several inter-related efforts of the proteomics community to develop standards for data and XML-interchange formats [ 14].
This problem becomes even more apparent when processing the data in scripting languages such as Python and R, which provide high-performance methods for bulk numerical operations on arrays, but no method for reading in data in interchange formats quickly.
convert data elements from their internal format into PCHR-specific format.
We demonstrate a 2-fold customization of Web services: by building task-specific processing pipelines from a repository of available analytics, and by configuring services to accept and produce a combination of input and output data interchange formats.
The mentioned customization of Web services is two-fold: (i) users are free to design their own processing pipelines from a repository of analytics, and (ii) the pipelines may be set up to accept and produce a combination of input and output data interchange formats.
Apart from syntactic and semantic analytics, the ever-growing library of components includes several data readers and consumers that support well-established as well as emerging data interchange formats such as XMI, RDF and BioC, which facilitate the interoperability of Argo with other platforms or resources.
In parallel with the advancement of various frameworks, repositories and platforms are efforts aimed at establishing data interchange formats for encoding information.
