A description of the construction of ORBIS can be found on the website https://orbis.stanford.edu/ And these publications: Scheidel, W., 2015. Orbis: the Stanford geospatial network model of the Roman world. Princeton/Stanford Working Papers in Classics. https://doi.org/10.1093/OBO/97801953896610075.2 Scheidel, W., 2014. The shape of the Roman world: modelling imperial connectivity. Journal of Roman Archaeology 27, 7–32.

"A 35 m resolution DEM was created with the ‘Topo to Raster’ interpolation method in ArcGIS 9.3 (selected because it recreates a more correct representation of ridges from input point and contour data, features that have a significant impact on the results of visibility analyses), using point and contour line data (source: ICA, Junta de Andalucía; contour interval 10 m). Lines of sight were derived by performing a probable viewshed (Fisher, 1992, Fisher, 1995) with 100 iterations for each site. This allowed us to distinguish between lines of sight of high and low probability. A single observer point per site was used for the visibility analysis, since for the vast majority of sites there was no data available of the occupied area and extent of settlement. However, the decision to use a single observer location is problematic and its impact on the results will need to be evaluated in future work for smaller study areas with a better knowledge of occupied settlement areas. An observer height of 1.7 m was assumed. Moreover, we assumed that the observed location height is that of the DEM cell on which the observed settlement is located, since very few settlements have evidence of architectural features that could be included in the analysis. The resulting visibility network (Fig. 6) was subsequently analysed using exploratory network measures, which revealed it consists of a number of components and three areas with a higher density of lines of sight (Brughmans et al., in press). The network used in the ERGMs includes lines of sight up to 20 km, at which distance fire and smoke signals are still visible, and with a probability higher than 50% (an arbitrary threshold, but a sensitivity analysis of network measures using different thresholds showed that it captures the key features of the network's structure (Brughmans et al., in press)). The final network, which will now be referred to as the “observed network” (prepared in the SNA software package UCINET), includes 159 nodes connected by 84 arcs."

Network creation description from https://doi.org/10.1016/j.jas.2014.05.027

Described in materials and methods of https://doi.org/10.1016/j.jas.2015.11.003

Manual collection of incrimination data.

Settlement locations derived from Pleiades ( https://pleiades.stoa.org/ ) based on the Barrington Atlas of the Greek and Roman World (Talbert 2000). Roads based on detailed digitization of major Roman roads by Pau de Soto: De Soto, P., Carreras, C., 2021. The Role of Politics in the Historical Transport Networks of the Iberian Peninsula and the Pyrenees from Roman Times to the Nineteenth Century. Social Science History 45, 233–260. https://doi.org/10.1017/ssh.2021.12

Nodes represent names, which are connected by a directed edge if a person with the outgoing node name gives the incoming node name to their child. The node of the name Sokrates, for example, has an edge directed to the node of the name Herakleides if at least one person called Sokrates has a son named Herakleides. In other words, the edges are based on genealogical relationships. The graph is also weighted: if multiple father-child pairs with the names Sokrates & Herakleides exist, then the relation between these two names is stronger.

To build these networks, the following steps were taken:

• lists of people attested in Zenon papyri from the online Trismegistos databases (https://www.trismegistos.org/) were extracted with F. Alvares Freire's “attestation per document” python webscraper (www.github.com/fernandaalvaf/Attestation-per-Document.) in 2021
• the outputs were cleaned and relevant information integrated into the project's relational database (MS Access)
• next, the ancient texts were read and text publications consulted for the purpose of extending and enriching the dataset through methods of close reading and literature review.
• for modelling the networks, relevant data were queried, exported and imported to Gephi (https://gephi.org/) for network analysis and visualisation

Described in details in Brughmans et al. 2015 https://doi.org/10.1007/s10816-014-9231-x

An edited version of the Roman roads originally digitized and geocoded by the Ancient World Mapping Centre (AWMC) based on the Barrington Atlas of the Greek and Roman World for the provinces Britannia, Germania Superior and Inferior, Raetia, Noricum, Pannonia Superior and Inferior, Moesia Superior and Inferior, and Dacia. The trajectories and intersections of these roads were validated in QGIS software by reconnecting loose ends due to minor errors in the coordinates of the original dataset. Due to fixing the loose ends of the network by an algorithm in QGIS using a buffer, this network is suitable for interconnected distance measurements and is not an exact representation of the Barrington Atlas data. The elements of the data are shapefile lines segmented by 1km.

This dataset was created by manually digitising CIL volume XV.1 by the author as a graduate student. The data is a rough and necessarily incomplete transcription of the information contained in the Corpus Inscriptionum Latinarum XV.1 Instrumentum domesticum, edited by H. Dressel, 1891. It should not be used to identify stamped bricks (one should use instead Steinby's 'Indici complementari ai bolli doliari urbani (CIL XV.1) Acta Instituti Romani Finlandiae 11). Its utility lies in being able to be searched quickly, to narrow down the range of possibilities. I offer it in that spirit. It took author approximately 50 hours to produce.