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Invisible Networks Project focuses on the study of the funerary cult of the Ancient Egyptian Old Kingdom from an eminently social perspective, we are interested in the people, the officiants who were in charge of maintaining and developing this cult. Our main research question is: what was the social and economic impact of the funerary cult on those who managed it? Who were these people and how did they interact with each other?
In order to answer these questions, the InvNet Database records the information of the officiants present in the iconography of the Old Kingdom monuments. There are three main categories, ranging from the most general to the most specific using a tree diagram. The category ‘monument’ contains information on each of the tombs under analysis. Within each monument the second category are the ‘scenes’, with a general description of the contents, and finally the category ‘officiant’ shows the specific data of each of the cultic actors in every scene who are labelled with a name.
To use the database, you can navigate through the Data Tree and look into the different necropolis and monuments or use the Finder to select your search criteria.
This resource is possible thank to Project PID2022 142974NA I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, UE
In order to answer these questions, the InvNet Database records the information of the officiants present in the iconography of the Old Kingdom monuments. There are three main categories, ranging from the most general to the most specific using a tree diagram. The category ‘monument’ contains information on each of the tombs under analysis. Within each monument the second category are the ‘scenes’, with a general description of the contents, and finally the category ‘officiant’ shows the specific data of each of the cultic actors in every scene who are labelled with a name.
To use the database, you can navigate through the Data Tree and look into the different necropolis and monuments or use the Finder to select your search criteria.
This resource is possible thank to Project PID2022 142974NA I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, UE