EMDB map data model

The EM Data Bank (EMDB) accepts and distributes 3D map volumes derived from several types of EM reconstruction methods, including single particle averaging, helical averaging, 2D crystallography, and tomography. Since its inception in 2002, the EMDB map distribution format has followed CCP4 definition (CCP4 map format) , which is widely recognized by software packages used by the structural biology community. CCP4 map format is closely related to the MRC map format used in the 3DEM community (MRC map format); CCP4 is slightly more restrictive, in that voxel positions are limited to a grid that includes the Cartesian coordinate origin (0,0,0). Further details can be found here.

EMDB header data model

Every EMDB entry has a header file containing meta data (e.g., sample, detector, microscope, image processing) describing the experiment. The header file is an XML file and the structure and content of the header file is described by a XSD data model. With a highly dynamic field such as cryo-EM there is a constant need to adapt and modify the schema to keep it up-to-date with the most recent developments. We consult extensively with the EM community regarding such issues and version the schema according to the policy described here.

Data model version 1.9

This has been a long-term stable version of the data model. It was be replaced in 2018 with an updated model but XML header files in version 1.9 continues to be distributed in parallel for at least one year to give EMDB users ample time to switch. It should be noted that the generation of the version 1.9 header files will be on a best effort basis but involves a back translation from recent versions that are richer in content and will therefore not contain all the information that can be found in the more recent versions.

Download schema
Browse schema documentation
Download Python code to facilitate reading and writing XML version 1.9 header files

Data model version 3.0 (current model)

This data model replaced version 1.9, however header files corresponding to both data models will be distributed in parallel with the view of stopping the distribution of the version 1.9 files in 2019 once users have had a chance to adopt version 3.0.

This version adds a number of features including:

  • An improved description of direct electron detectors, specimen preparation and tomography experiments.
  • A hierarchal description of the overall sample composition in combination with a low-level description of the macromolecular composition to allow the description of both molecular and cellular samples.
  • Specific data items describing the half-maps and segmentations included with the entry.
Download schema
Browse schema documentation
Download Python code to facilitate reading and writing XML version 1.9 header files

EMDB segmentation data model

Segmentation is the decomposition of 3D volumes into regions that can be associated with defined objects. Following several consultations with the EM community (Patwardhan et al., 2012; Patwardhan et al., 2014; Patwardhan et al., 2017), the EMDB is in the process of developing tools to support deposition of volume segmentations with structured biological annotation which is here defined as the association of data with identifiers (e.g., accession codes from UniProt) and ontologies taken from well established bioinformatics resources. To our knowledge, none of the segmentation formats widely used in electron microscopy and related fields currently support structured biological annotation. Third party use of segmentations is further impeded by the prevalence of segmentation file formats and their lack of interoperability. EMDB therefore proposed an open segmentation file format called EMDB-SFF to capture basic segmentation data from application-specific segmentation file formats and provide the means for structured biological annotation. In this way, EMDB-SFF will not only enable depositions of segmentations but also act as a file interchange format between different applications and facilitate analysis of 3D reconstructions. Furthermore EMDB-SFF supports the description of multiple transforms for a segment, thus allowing a segment to be used to describe the placement of a sub-tomogram average onto a tomographic reconstruction.


EMDB-SFF files have the follow features:

  • Segmentation metadata:
    • name
    • version (of schema)
    • details (free-form text)
    • global external references, e.g. specimen scientific identifier
    • bounding box
    • primary descriptor contained i.e. one of ‘threeDVolume’, ‘meshList’, ‘contourList’, or ‘shapePrimitiveList’ (see schema documentation)
    • path to original segmentation file
    • list of transforms referenced by segments e.g. transform to place the sub-tomogram average in the tomogram
  • Hierarchical ordering of segments through the use of segment IDs and parent IDs;
  • Four geometrical representations of segments (volumes, contours, meshes, shapes);
  • Can store subtomogram averages and how they map into the parent tomogram through the use of transforms;
  • List of associated external references per segment;
  • List of associated complexes and macromolecules in a related EMDB entry

Each segment in a segmentation can consist of two types of descriptors:

  • textual descriptors;
  • geometric descriptors.

Textual descriptors consist of either free-form text or standardised terms. Standard terms should be provided from a [published] ontology or list of identifiers.

Geometric descriptors can take one or more of the following representations:

  • ‘threeDVolume’ for 3D volumes;
  • ‘contourList’ for lists of contours each of which is a series of 3D points;
  • ‘meshList’ for lists of meshes each of which consists of a set of vertices and polygons;
  • lists of shape primitives (ellipsoid, cuboid, cone, cylinder).


The current schema (version 0.6.0a4) is available here.
Complete documentation of the schema is available here.

Auxiliary Tools


sfftk provides a shell command and a Python API to process EMDB-SFF files.

The following utilities are available using sfftk:

  • sff convert: Conversion of application-specific segmentation file formats to EMDB-SFF. Currently, sfftk supports the following formats:
    • AmiraMesh (.am)
    • Amira HyperSurface (.surf)
    • Segger (.seg)
    • EMDB Map masks (.map)
    • Stereolithography (.stl)
    • IMOD (.mod)
  • sff notes: Annotation of EMDB-SFF files.
  • sff view: Brief summaries of segmentation files.

Read the full documentation here


The latest development version (version 0.2.1.dev5) of sfftk may be downloaded/installed from PyPI or the source may be obtained from GitHub.