Systems and methods are provided for scheduling objects having pair-wise and cumulative constraints. The systems and methods presented can utilize a directed acyclic graph to increase or maximize a utilization function. Violation of cumulative constraints can be identified at the moment of constraint violation such that events resulting in constraint violations can be removed from the schedule while the schedule is being determined. By removing the events triggering constraint violations at the point of constraint violation, the systems and methods provided can determine optimal or near-optimal schedules in a relatively quick and efficient manner compared to systems and methods that check for violations of cumulative constraints after determining a schedule. The objects can comprise satellites in a constellation of satellites. In some implementations, the satellites are imaging satellites, and the systems and methods for scheduling can use crowd-sourced data to determine events of interest for acquisition of images.

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a minimal bounding rectangle associated with the query is identified using a tree-order scanning technique. A spatial data set that corresponds to the received query is then mapped to the physical storage in the database using the identified minimal bounding rectangle. Next, the spatial data set is then retrieved. Related apparatus, systems, techniques and articles are also described.

A data enrichment system may include an attribute relevance module to measure relevance of an attribute to a data object to be enriched. The data object may include the attribute including a known or an unknown value. An output value confidence module may calculate a confidence of an output value of a source used for enrichment of the data object. The output value may represent the known and/or unknown values of the attribute. The system may use the measured relevance of the attribute and the calculated confidence of the output value to determine assignment of the known or unknown values to the attribute.