Abstract: The design, creation, use, and execution of command line parsers based on subcommand classes instead of boilerplate code is described. Commands and subcommands have corresponding class definitions, which upon instantiation based on command line content will provide and execute code to perform the command. Subcommand dispatching may be accomplished using delegates, using an interface implementation, or otherwise. Class attributes may define help text, argument aliases, and other metadata. Subcommand types may be passed as generic arguments, as objects, or otherwise. Arguments may be made optional or be required by providing or omitting class constructor parameter default values. By using classes to implement subcommands and avoiding reliance on large error-prone if or switch statements, parser development is made easier and more efficient.

Abstract: The design, creation, use, and execution of command line parsers based on subcommand classes instead of boilerplate code is described. Commands and subcommands have corresponding class definitions, which upon instantiation based on command line content will provide and execute code to perform the command. Subcommand dispatching may be accomplished using delegates, using an interface implementation, or otherwise. Class attributes may define help text, argument aliases, and other metadata. Subcommand types may be passed as generic arguments, as objects, or otherwise. Arguments may be made optional or be required by providing or omitting class constructor parameter default values. By using classes to implement subcommands and avoiding reliance on large error-prone if or switch statements, parser development is made easier and more efficient.

Abstract: Content providers define a set of scenarios that are addressed by their datasets. The scenarios include user-friendly, human-readable attributes such as a title, description, and visualization. The scenarios may also include a technical description that can be used to generate sample queries that can then be executed against the dataset. The technical description may be machine translated to arbitrary data querying protocols while maintaining the semantic meaning of the query. A user interface may be provided to allow users to intuitively generate the scenarios. In one embodiment, an extensible framework provides for the creation of protocol-specific translation plug-ins that are used to generate implementations of the scenario suitable for selected protocols. Known market-relevant translator plug-ins may also be implemented.

Abstract: Content providers define a set of scenarios that are addressed by their datasets. The scenarios include user-friendly, human-readable attributes such as a title, description, and visualization. The scenarios may also include a technical description that can be used to generate sample queries that can then be executed against the dataset. The technical description may be machine translated to arbitrary data querying protocols while maintaining the semantic meaning of the query. A user interface may be provided to allow users to intuitively generate the scenarios. In one embodiment, an extensible framework provides for the creation of protocol-specific translation plug-ins that are used to generate implementations of the scenario suitable for selected protocols. Known market-relevant translator plug-ins may also be implemented.

Abstract: Individual datasets are accessed using an application programming interface (API). Multiple APIs may be combined into a composite API that allows a user to access multiple datasets using a single query. The composite API may be designed to provide a simpler way to consume information from multiple datasets in response to a particular scenario or problem. The composite API may comprise multiple levels of intermediate APIs that call on each other to access desired datasets. A user may select the datasets that the composite API accesses and/or the composite API may require certain specific datasets. The composite API may be offered for sale or use by other users via a website, such as a data market.

Abstract: Techniques are described herein that are capable of facilitating development of data-rich applications. A data-rich application is an application (e.g., a software application) that is configured to perform an analysis of data (e.g., structured data, unstructured data, or a combination thereof) and to provide information based on the analysis. In accordance with the aforementioned techniques, a public online environment may be provided in which application developers are allowed to access representative samples of data owned by data owners at a substantially reduced cost (e.g., free) to facilitate development of the data-rich applications.

Abstract: Content providers define a set of scenarios that are addressed by their datasets. The scenarios include user-friendly, human-readable attributes such as a title, description, and visualization. The scenarios may also include a technical description that can be used to generate sample queries that can then be executed against the dataset. The technical description may be machine translated to arbitrary data querying protocols while maintaining the semantic meaning of the query. A user interface may be provided to allow users to intuitively generate the scenarios. In one embodiment, an extensible framework provides for the creation of protocol-specific translation plug-ins that are used to generate implementations of the scenario suitable for selected protocols. Known market-relevant translator plug-ins may also be implemented.

Abstract: Individual datasets are accessed using an application programming interface (API). Multiple APIs may be combined into a composite API that allows a user to access multiple datasets using a single query. The composite API may be designed to provide a simpler way to consume information from multiple datasets in response to a particular scenario or problem. The composite API may comprise multiple levels of intermediate APIs that call on each other to access desired datasets. A user may select the datasets that the composite API accesses and/or the composite API may require certain specific datasets. The composite API may be offered for sale or use by other users via a website, such as a data market.