Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: An inline tree data structure and one or more auxiliary data structure encode a multitude of data records of a dataset; data fields of the dataset define a tree hierarchy. The inline tree comprises one binary string for each data record that are all the same length, are arranged in an ordered sequence that corresponds to the tree hierarchy, and include an indicator string indicating position in the tree hierarchy of each data record relative to an immediately adjacent data record. A search program is guided through the dataset by interrogating each indicator string in the inline tree data structure so as to reduce unnecessary interrogation of data field values.

Abstract: A method includes generating from a time-series dataset multiple corresponding time-slice datasets. Each time-slice dataset has a corresponding time-slice time index and includes field-value data strings and associated field-value-time-index data strings, or pointers indicating the corresponding strings in an earlier time-slice dataset, that are the latest in the time-series dataset that are also earlier than the corresponding time-slice time index. A query of the time-series dataset for latest data records earlier than a given query time index is performed by using the time-slice datasets to reduce or eliminate the need to directly access or interrogate the time-series dataset.

Abstract: A binary data file embodies an inline tree data structure storing fields of a hierarchical dataset. The inline tree comprises first-level binary string segments, each comprising substantially contiguous second-level binary string segments, corresponding to subranges of first and second subsets of data fields. Size is reduced by substituting: binary string indices for alphanumeric strings; a data clump index for a set of correlated/anticorrelated strings; field masks for unoccupied data fields. A dedicated conversion program generates the inline tree from conventional database formats, which is read entirely into RAM to be searched/filtered by a dedicated search/filter program. Small size (<2 bytes/field/record) and contiguous arrangement enables searching/filtering of >106 records (>100 data fields) in <500 nanoseconds/record/core. Recursive subdivision of selection field ranges can guide searches that include those selection fields.

Abstract: A data structure comprises a clump header table and an inline tree data structure. The inline tree, representing filterable data fields of hierarchically organized data records, comprises an alternating sequence of first-level binary string segments, each followed by one or more corresponding second-level binary string segments. Each clump header record includes an indicator of a location in the inline tree of corresponding binary string segments. A dedicated, specifically adapted conversion program generates the clump header file and the inline tree for storage on any computer-readable medium, and the inline tree can be read entirely into RAM to be searched or filtered. A dedicated, specifically adapted search and filter program is employed to list or enumerate retrieved data records. Run-time computer code generation can reduce time required for searching and filtering. One example includes spatial searching and filtering of data records that include spatial coordinates as data fields.

Abstract: A data structure comprises a clump header table, an inline tree data structure, and one or more auxiliary data structures. Each clump header record includes an indicator of a location in the inline tree data structure of corresponding binary string segments. Clump header records or auxiliary header records include indicators of corresponding locations in the corresponding auxiliary data structure. Each auxiliary data structure can be altered without necessarily altering the inline tree or clump header table. A dedicated, specifically adapted conversion program generates the clump header file, the inline tree data structure, and the one or more auxiliary data structures. The data structure can be stored on any computer-readable medium, and can be read entirely into RAM to be searched (with or without filtering on one or more filter data fields). A dedicated, specifically adapted search and filter program is employed, which can list or enumerate the retrieved data records.

Abstract: Generating and storing, for a multitude of polygonal areas, spatial coordinates of a multitude of piecewise-linear spatial boundary segments. The polygonal boundary of each area comprises boundary segments; each boundary segment forms a portion of the polygonal boundary of at most two adjacent spatial areas. Can further include one or both of (i) an indicator, for each spatial boundary segment, of the at most two corresponding adjacent spatial areas that are separated by that boundary segment or (ii) an indicator, for each spatial area, of one or more boundary segments that together form the entire polygonal boundary of that spatial area. The electronic indicia of the second dataset can be used, inter alia, (i) to determine in which of a multitude of at least partly contiguous spatial areas is located a given spatial point, or (ii) to graphically render the polygonal borders of the areas.

Abstract: A data structure comprises a clump header table, an inline tree data structure, and one or more auxiliary data structures. Each clump header record includes an indicator of a location in the inline tree data structure of corresponding binary string segments. Clump header records or auxiliary header records include indicators of corresponding locations in the corresponding auxiliary data structure. Each auxiliary data structure can be altered without necessarily altering the inline tree or clump header table. A dedicated, specifically adapted conversion program generates the clump header file, the inline tree data structure, and the one or more auxiliary data structures. The data structure can be stored on any computer-readable medium, and can be read entirely into RAM to be searched (with or without filtering on one or more filter data fields). A dedicated, specifically adapted search and filter program is employed, which can list or enumerate the retrieved data records.

Abstract: A data structure comprises a clump header table and an inline tree data structure. The inline tree, representing filterable data fields of hierarchically organized data records, comprises an alternating sequence of first-level binary string segments, each followed by one or more corresponding second-level binary string segments. Each clump header record includes an indicator of a location in the inline tree of corresponding binary string segments. A dedicated, specifically adapted conversion program generates the clump header file and the inline tree for storage on any computer-readable medium, and the inline tree can be read entirely into RAM to be searched or filtered. A dedicated, specifically adapted search and filter program is employed to list or enumerate retrieved data records. Run-time computer code generation can reduce time required for searching and filtering. One example includes spatial searching and filtering of data records that include spatial coordinates as data fields.

Abstract: A binary data file embodies an inline tree data structure storing fields of a hierarchical dataset. The inline tree comprises first-level binary string segments, each comprising substantially contiguous second-level binary string segments, corresponding to subranges of first and second subsets of data fields. Size is reduced by substituting: binary string indices for alphanumeric strings; a data clump index for a set of correlated/anticorrelated strings; field masks for unoccupied data fields. A dedicated conversion program generates the inline tree from conventional database formats, which is read entirely into RAM to be searched/filtered by a dedicated search/filter program. Small size (<2 bytes/field/record) and contiguous arrangement enables searching/filtering of >106 records (>100 data fields) in <500 nanoseconds/record/core. Recursive subdivision of selection field ranges can guide searches that include those selection fields.

Abstract: Generating and storing, for a multitude of polygonal areas, spatial coordinates of a multitude of piecewise-linear spatial boundary segments. The polygonal boundary of each area comprises boundary segments; each boundary segment forms a portion of the polygonal boundary of at most two adjacent spatial areas. Can further include one or both of (i) an indicator, for each spatial boundary segment, of the at most two corresponding adjacent spatial areas that are separated by that boundary segment or (ii) an indicator, for each spatial area, of one or more boundary segments that together form the entire polygonal boundary of that spatial area. The electronic indicia of the second dataset can be used, inter alia, (i) to determine in which of a multitude of at least partly contiguous spatial areas is located a given spatial point, or (ii) to graphically render the polygonal borders of the areas.