Abstract: A method for graph-based data analysis based on interpreting a structure definition language comprises storing a plurality of structures, wherein the plurality of structures define a plurality of positions and a plurality of relationships between the plurality of positions; generating one or more compiled structures based on the plurality of structures; receiving, from a client computing device, a query specifying one or more input positions; in response to receiving the query: selecting, based on the one or more input positions, one or more particular compiled structures of the one or more compiled structures; determining a result set for the query based on executing the one or more particular compiled structures, wherein executing the one or more particular compiled structures causes evaluating at least the one or more input positions; and causing the result set to be provided to the client computing device.

Abstract: A system automatically processes rules for allocation of resources to mitigate damages resulting from a catastrophic event. Overlapping interests of various stakeholders are processed in a deterministic manner to ensure repeatable processing and modeling. In one embodiment the resources are disaster aid items; in another they are obligations regarding insurance.

Abstract: A computing system and platform uses various types of data stores to allow efficient querying of, and accelerated access to, extremely large data sets. One such data store is a dimension store that combines key-value and columnar stores, access to which is provided by several selectable mechanisms chosen based the nature of the data of interest. These include bitmap-based access, us of an optimized columnar data format, and access via namespace identifiers. A compressed, optimized page data format is provided for storing and analyzing large fact-based data. The complex dimension store is used to provide complex relationships and interpretation of the fact-based data, enabling high-performance advanced queries, with bitmap indexes passed between the two stores. Dimension data is stored in an encrypted manner throughout the system, and can be exchanged among parties in a secure manner.

Abstract: A computing system and platform uses various types of data stores to allow efficient querying of, and accelerated access to, extremely large data sets. One such data store is a dimension store that combines key-value and columnar stores, access to which is provided by several selectable mechanisms chosen based the nature of the data of interest. These include bitmap-based access, us of an optimized columnar data format, and access via namespace identifiers. A compressed, optimized page data format is provided for storing and analyzing large fact-based data. The complex dimension store is used to provide complex relationships and interpretation of the fact-based data, enabling high-performance advanced queries, with bitmap indexes passed between the two stores. Dimension data is stored in an encrypted manner throughout the system, and can be exchanged among parties in a secure manner.

Abstract: A system automatically processes rules for allocation of resources to mitigate damages resulting from a catastrophic event. Overlapping interests of various stakeholders are processed in a deterministic manner to ensure repeatable processing and modeling. In one embodiment the resources are disaster aid items; in another they are obligations regarding insurance.