The data for this study are derived from The Orthida Database, which contains information on the more than 300 Orthida genera, recently revised by Williams and Harper (2000). The database also contains information on other brachiopod orders, however, these are not used here. The data are collected from published sources only and are of varying quality in their spatial and temporal resolution.

The records of The Orthida Database that are precise to a specific area such as a site, formation, country or a single plate which is well defined, and which have a temporal precision of epoch level or stage level, comprise a truncated dataset amounting to about 40% of the total dataset. The truncated data are used here. Of these records, European and North American data comprise about 67%, which indicates that there is a skewed distribution in the geographical distribution of orthide data, which should, however, not be relevant to this study which primarily deals with areas of consistent high sampling intensity. The dataset does not utilize the range-through assumption, including only genera actually reported from the particular stage or epoch. The data quality and related problems are discussed in further detail below.

With respect to the temporal resolution of the data, clearly older publications contain less precise temporal data. This is primarily due to updates in the chronostratigraphic framework since their publication. This is also true for the age of rock formations: For the Cambrian, only approximately 35% of the total dataset is at Epoch or better temporal resolution, while for the Devonian this proportion is over 50%.

The data used in this study are drawn from the Ordovician-Silurian sections of the truncated dataset from the GIOR plates. Using this focused dataset allows a better temporal resolution than would have been possible with the total dataset. Although the total dataset results in higher total diversities, tests during construction of The Orthida Database showed only minor changes in the overall biogeographical patterns between the two datasets (see also Sepkoski 1993).