Products and Services / Rich Map Engine

Rich Map Format

Rich Map Format (RMF) is deCarta's proprietary and patented data format. It is a highly compact, binary format optimized for spatial query processing and lies at the heart of deCarta technology. In fact, some of deCarta's advantages derive directly from exclusive utilization of RMF.

RMF is partly a compaction (not compression) scheme. RMF reduces the "white noise" present in other data formats by a clever and efficient encoding of the data. Fixed-width fields clearly demonstrate the concept of "white noise". A fixed-width field of 25 characters is always 25 characters long regardless of whether any information is present. In the RMF, only useable information makes it in; "white noise" disappears.

RMF further reduces the file size by eliminating redundancies that can add many megabytes of redundant information in some formats. For example, a stretch of road may have the same name for nine segments. Instead of assigning the same name to each of those nine segments, RMF assigns the name once for a designated origin and destination.

RMF reduces the file size one more time by converting the data into a binary format. This compaction methodology results in file sizes that typically range from 1/10th to 1/15th the file size of the original source data.

The primary advantage of RMF is that it is spatially organized. A spatial format organizes data in a multi-dimensional fashion such that features near each other in reality get stored close together in the database. For example two gas stations located on opposite corners of an intersection, as illustrated in the following figure.

Sample Points of Interest

In a sequential file sorted by name, address, or street name, these points of interest (POIs) would be located at opposite ends of the data set with thousands, or even hundreds of thousands, of records in between. In a spatially organized format, the items are located adjacent to each other, just like they are in the real world. This means that once you find a location in a spatially formatted dataset, you can quickly find other close by POIs, addresses, features, etc.