Fig 1.
The conceptual structure of ROAD.
The rectangles represent the generalized themes of the database. The central oval and lines connecting it to the themes depict relationships. Because the rectangles depict one or many entities, most of the lines represent more than one relationship. All lines joining the central oval represent many-to-many relationships. The other lines represent one-to-many relationships.
Fig 2.
The table “locality” and its attributes.
In addition to the attributes shown, all tables in ROAD include fields for comments, the name of the owner, the date the record was created, and a history of modification. The ROAD Table Descriptions (S1 File) provide detailed definitions of all tables and their attributes, specifications for data entry and examples of possible entries.
Fig 3.
The table “geological layer” and its attributes (left) and a dynamically generated geological profile for the locality Rhafas Cave (right).
Rhafas Cave consists of a single profile which contains four geological layers. Each of the visualized layers depicts information about its name, sedimentology, thickness and age. By clicking on a geological layer, a user can find out more information about the corresponding archaeological layers and the assemblages they contain.
Fig 4.
The table “assemblage” and its attributes.
The first two attributes specify the locality and a unique identification number for each assemblage at that locality. The attribute ‘name’ contains a unique name that identifies the assemblage, e.g. Layer VI lithics or Horizon B human remains. The attribute ‘category’ lists which tables in ROAD contain further information about the assemblage. If an assemblage consists of stone artifacts, the ‘lithic piece count’ reflects the total number of artifacts contained in that assemblage. The degree to which an assemblage was collected systematically is scored (0–3) according to the sampling procedure, while its representativeness (0–3) is scored to consider any bias in collection.
Fig 5.
Assemblages stored in ROAD are categorized into four basic classes.
The classes include archaeological finds as well as human, fauna and plant remains. The archaeological finds are further divided into subclasses for stone artifacts, organics tools, symbolic artifacts, miscellaneous finds and features.
Fig 6.
Classification of stone artifacts.
Lithic assemblages are divided into raw material, typology, technology and function.
Fig 7.
Tables for analyzing stone artifacts listing the attributes of each table.
Raw materials include the distance to source, while typology describes the types of tools, cores and debitage. Technological characteristics of the stone artifacts (e.g. Levallois or Kombewa) and the results of functional analyses (e.g. use wear or residue studies) can also be entered.
Fig 8.
Tables for entry of non-stone artifacts listing their respective attributes.
Organic tools can be made of bone, tooth, ivory, shell or wood, while symbolic artifacts include art, music and ornaments. Miscellaneous finds such as ochre, minerals or unmodified shell, and features such as burials or stone constructions can also be entered.
Fig 9.
Tables for the entry of human remains in ROAD.
Because researchers may interpret human remains differently in different publications, ROAD includes a second table “publication_desc_humanremains”, which links a relevant publication to its record in the table “humanremains”. The table “publication_desc_humanremains” includes further interpretations about the published description of the human fossils.
Fig 10.
The table “paleofauna” is linked to the look-up table “taxonomical_classification” and to the table “publication”.
The table “paleofauna” is linked to the look-up table “taxonomical_classification”. The link joining these tables represents a one-to-many relationship. The table “paleofauna” is also linked to the table “publication”. The link joining the tables “paleofauna” and “publication” represents a many-to-many relationship. To describe this relationship, ROAD includes the table “publication_desc_paleofauna” in which every record has a link to the relevant publication, as well as to its record in the table “paleofauna”. In addition, “publication_desc_paleofauna” specifies the MNI and the method used to calculate it because MNIs for faunal remains can differ depending on the publication and method applied.
Fig 11.
Tables for botanical finds and their relationships.
The link between “plantremains” and “paleoflora” as well as the link between “paleoflora” and “plant_taxonomy” each represent a one-to-many relationship.
Table 1.
List of ROAD user groups and their capabilities.
Group 1 can access ROAD without a login, while groups 2–4 require a user id and password to log in.
Fig 12.
The Map Module (background) and a pop-up window (foreground) used to conduct a simple search in ROAD. A simple search can be executed based on questions about the where (localities), what (assemblages) and when (age). Map credit: OpenStreetMap.
Fig 13.
View of the SQL query tool for composing queries.
While knowledge of programming is not required to use ROAD, it is necessary to learn how to use the interface itself. This can be accomplished with help from the ROAD Manual (S2 File) and other supporting documentation.
Fig 14.
Examples of ROAD search possibilities.
Examples from the locality Wonderwerk Cave in South Africa. A view of interactive geological profiles (left), associated archaeological layers and assemblages in a selected geological layer (upper right) and map view (lower right). Map credit: OpenStreetMap.
Fig 15.
Spatial and chronological coverage of assemblages contained in ROAD as of 21 February 2023.
The assemblages include archaeological finds and human, faunal and plant remains. (A) Spatial distribution of localities in Africa and Eurasia showing the richness of the assemblages. (B) Number of localities and assemblages per continent. (C) Temporal distribution of assemblages based on their mean ages and graphed as stacked columns. Due to the log-scale of the x-axis, the time contained within each bar increases with age. Map credit: Made with Natural Earth (public domain).
Table 2.
List of the number of localities and assemblages entered in ROAD.
Fig 16.
Absolute dating methods, mean ages and age uncertainty.
We include the most common dating methods (n = 10,720) entered in ROAD, but exclude mixed methods and less common absolute dating methods (n = 1566) as well as relative ages. When the age uncertainty on the y-axis (i.e. the difference in positive and negative standard deviation) is asymmetric, we report the higher uncertainty. (See text for explanation of dating methods.).
Fig 17.
ROAD’s database structure enables interdisciplinary work.
The Venn diagram visualizes how many localities are associated with the four main categories (archaeological, human, faunal and plant remains) and how they intersect. The darker the color, the greater the number of localities. Note that the sizes of the areas are not represented proportionally. Percentages are related to the total number of 1724 localities associated with at least one assemblage category.
Fig 18.
ROAD is sourced from 5020 publications spanning the last 158 years. (A) Distribution plot of the years of publication. (B) Lorenz curve showing the relative concentration of sources. The y-axis shows the cumulative percentage of titles, while the x-axis shows the cumulative percentage of 1424 sources. A source can be a single book, thesis or report, but also a journal with hundreds of titles (i.e. articles). The further the Lorenz curve deviates from the dashed line of equality, the more disparate or concentrated the distribution.
Fig 19.
Chronological distribution of archaeological assemblages.
ROAD contains Paleolithic assemblages attributed to six broadly defined cultural periods. Distributions of (A) Upper Paleolithic and Later Stone Age localities, (B) Middle Paleolithic and Middle Stone Age localities, and (C) Lower Paleolithic and Early Stone Age. (D) The frequency of the main cultural periods by locality, with colors coded to inset maps (A), (B) and (C). Map credit: Made with Natural Earth (public domain).
Fig 20.
Distribution of some technocomplexes in ROAD.
The bar chart shows some of the most frequent cultural entities (technocomplexes) contained in ROAD.
Table 3.
List of studies making use of ROAD data.
This table shows completed and ongoing research supported by ROAD, in chronological order.
Fig 21.
Development of the ROAD database over time.
(A) Map showing the year when an assemblage was first created within a country. Color codes correspond to the timeline on the right, with gray countries not yet containing sites. (B) Number of assemblages created per quarter year over the lifespan of ROCEEH. Map credit: Made with Natural Earth (public domain).
Fig 22.
Missing data—Assembling the pieces of the puzzle.
Despite an intensive focus on data entry, the majority of the prehistoric world remains uncharted, as shown by the blank areas of this map. Visualization based on a Kernel Density Estimate of ROAD assemblages. Sites with higher assemblage densities appear more intense in color. Note that Australia is not within the database’s scope. Map credit: Made with Natural Earth (public domain).