It is critical to capture the context into which data has been generated in order to be able to filter out non-relevant data and compress data, to automatically generate metadata supporting a rich data description, and to track and record data provenance [2].
Over the course of the last year or so, we've seen Google and others focus on video recognition, though, and that work is now paying off in the form of services like Rekognition, which can automatically generate metadata from video files.
While some solutions such as [7, 8] claims that generating useful annotations as metadata from unstructured web documents is possible, there is still no scalable and semi-automatic solutions to generate semantic metadata of web documents based on the semantic related to the topic implicitly embedded in the content and relationships of web documents.
However, for content providers and developers, it is almost impossible to generate such metadata manually.
In the case of a molecule as an object, there are algorithms which can be used to generate appropriate metadata, the most useful and prominent of which is the InChI (International Chemical Identifier [11].
The driver for this development for ChemSpider would be that it would make it much easier to integrate other ELNs to be able to deposit to ChemSpider, rather than writing a separate plugin for each, particularly if the vendors and developers of other ELNs built the ability to generate this metadata into their APIs.
This section discusses the workflow we followed to retrieve relevant gene-expression datasets and to generate detailed metadata annotations for each study.
They are excited about the possibilities that DataUp represents for linking researchers' workflows directly to repositories, with capabilities for generating metadata and performing best practices checks.
Future development plans include the ability to expand metadata options and allow for generating metadata files that comply with different standards for various disciplines.
Certainly the immediate goal is to amplify the street cred of these messages, generating metadata that can be injected back into the flow in ways more consumable than a realtime LIFO view.
