International
Tables for
Crystallography
Volume G
Definition and exchange of crystallographic data
Edited by S. R. Hall and B. McMahon

International Tables for Crystallography (2006). Vol. G, ch. 2.6, p. 63

Section 2.6.4. DDL2 organization

J. D. Westbrook,a* H. M. Bermana and S. R. Hallb

aProtein Data Bank, Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, Department of Chemistry and Chemical Biology, 610 Taylor Road, Piscataway, NJ 08854-8087, USA, and bSchool of Biomedical and Chemical Sciences, University of Western Australia, Crawley, Perth, WA 6009, Australia
Correspondence e-mail:  jwest@rcsb.rutgers.edu

2.6.4. DDL2 organization

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Figs 2.6.4.1[link]–2.6.4.3[link][link] provide schematic illustrations of the definitional features provided by DDL2. These figures represent the elements of the DDL in terms of its own language constructs (i.e. categories and the relationships between attributes within those categories). This self-defining presentation has the important consequence of validating the internal consistency of the DDL data model.

[Figure 2.6.4.1]

Figure 2.6.4.1 | top | pdf |

DDL2 attributes used to specify item information. In this figure, boxes surround data items belonging to the same category. Category identifiers are given in a large typesize and item names are given in a smaller typesize. Parent–child relationships are specified by lines connecting data items with the arrow pointing at the parent item. Key items within a category are marked with a bullet.

[Figure 2.6.4.2]

Figure 2.6.4.2 | top | pdf |

DDL2 attributes used to specify category, subcategory and category group information. Category identifiers are given in a large typesize and item names are given in a smaller typesize. Parent–child relationships are specified by lines connecting data items with the arrow pointing at the parent item. Key items within a category are marked with a bullet.

[Figure 2.6.4.3]

Figure 2.6.4.3 | top | pdf |

DDL2 attributes used to specify dictionary and data-block information. Category identifiers are given in a large typesize and item names are given in a smaller typesize. Parent–child relationships are specified by lines connecting data items with the arrow pointing at the parent item. Key items within a category are marked with a bullet.

Fig. 2.6.4.1[link] shows the organization of the attributes available to define each data item. These include: a description, examples, data type, allowed values and ranges, default values, internal structural features (e.g. vector and matrix properties), units, and other dependency relationships. These DDL attributes are shown as a collection of DDL categories enclosed in boxes in the figure. For instance, the description or textual definition for a data item is specified in a category named ITEM_DESCRIPTION. This DDL category contains the attributes `name' and `description'. The attribute `name' corresponds to the DDL data item _item_description.name. This item is the key item in the category named ITEM_DESCRIPTION. In Fig. 2.6.4.1[link] this is denoted by a bullet. The name attribute in the ITEM_DESCRIPTION category is related to the parent definition of this data item in the category named ITEM. This is reflected in Fig. 2.6.4.1[link] by the line pointing to the parent data item.

The data-block level ties the contents of a dictionary to the data_ section in which it is contained. The identifier for the data block and hence the dictionary is added implicitly to the key of each category. This builds into the data model a convenient means for distinguishing similar information recorded in separate data blocks. This feature is important in organizing the results from different crystallographic experiments, each being reported as a separate block of data.

Fig. 2.6.4.2[link] illustrates the organization of attributes describing categories, subcategories and category groups. Similarly, Fig. 2.6.4.3[link] shows the organization of DDL2 attributes at the data-block and dictionary level. All of these attributes are discussed in terms of their application in building data dictionaries in the next section.








































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