In addition to the requirements of the forthcoming guidance, the Open Government Directive also requires federal agencies to publish at least three "high value" datasets on Data.gov by the end of January.
OMB recently launched a self-service data publishing tool for agencies called the Dataset Management System, and plans to overhaul Data.gov with new features, though the timeline is unclear. For users, it will add collaboration tools, more opportunity for feedback, and improved search. The search tool will be integrated with USASearch.gov and could include a number of ways to improve search usability via features like top queries and tag clouds. Data.gov will also include a new hierarchical topic structure, user tagging, and the ability to search within datasets for keywords. Eventually, OMB plans to add geospatial search capabilities and potentially a data visualization platform.
For agencies, it will add shared data hosting and metadata storage services, a performance tracking system, and potentially an audit tool to help agencies evaluate their data management practices and to integrate already public data into Data.gov. For developers, OMB will create multiple APIs and a way for developers to submit usage statistics and feedback to the government to help improve Data.gov.
Kundra also plans to begin issuing prize money to developers who have the best ideas. However, unlike some of the other early open government application development prizes, such as Apps for D.C., which paid out lump sums to prize winners only later to see developers move on to other things, the government will "move away from a one-time prize to a way of running operations," ostensibly by creating business relationships with the prize winners to continue making their tools more useful.
Finally, OMB plans to embark on a new pilot to put in place forward-thinking semantic Web features via semantic.data.gov, which will incorporate "semantically enabled techniques within the sites and the datasets" by leveraging cross-domain data models and "curating" that data a la Wolfram Alpha to help users create meaningful results and new, user-created data computations.