Abstract: An analysis module, when triggered by a synchronization framework when a new data item is added to a project data store, runs a series of analysis feature extractors on the new content. An analysis may be conducted, and features of interest may be extracted from the data item. The analysis utilizes natural language processing, as well as other technologies, to provide an automatic or semi-automatic extraction of information. The extracted features of interest are saved as metadata within the project data store, and are associated with the data item from which it was extracted. The analysis module may be utilized to discover additional information that may be gleaned from content that is already in the project data store.

Abstract: An automatic discovery of content to add to a data store for a project is disclosed. A data item may be parsed for data features that are contextually relevant to a given project or task. Discovered interesting data may be extracted and mapped to various search mechanisms. A search may be built and applied to various data sources to discover data items based on the contextually relevant data features. Search results from various search mechanisms may be displayed in a single user interface and may be presented to a user.

Abstract: Project-related data may be aggregated from various data sources, given context, and may be stored in a data repository or organizational knowledge base that may be available to and accessed by others. Documents, emails, contact information, calendar data, social networking data, and any other content that is related to a project may be brought together within a single user interface, irrespective of its data type. A user may organize and understand content, discover relevant information, and act on it without regard to where the information resides or how it was created.