Facilitating archaeological research
Making images of (lost) archaeological sites more easily accessible
While conflicts in the Middle East destroy cultural heritage, there is a strong desire within the archaeological community to preserve existing knowledge. Researchers also have very little access to images from archaeological sites due to the large amount of these images still only existing in the form of slides or prints stored in physical archives.
Landscape was approached by Dr. Tim Clayden, an archaeologist, to develop a website that can store a large amount of archaeological images digitally, in order to make it easier for researchers - as well as the general public - to acquire images for their work or store their own.
Landscape developed a fully responsive web page capable of uploading and displaying large amounts of images, easily searchable and filterable on different tags. For this, we used the Angular framework, using i.a. NodeJS.
Rijksmuseum voor Oudheden
As of October 2017, the OAID is part of the Nineveh exhibition in the Dutch National Museum of Antiquities (Rijksmuseum voor Oudheden - RMo). The organisation has exposed OAID since they find it a great means of preserving images of lost archaeological sites.
How is this data?
As most people know, photos taken nowadays automatically contain a lot of metadata, such as the date the picture was taken, the location, etc. But these specific archaeological images can also be tagged with a lot more metadata, such as period the site stems from, type of building, and structure or material.
After having collected enough images, one could analyse this metadata to recognise patterns, such as trade routes and migrations.
We are currently extending the website with ontologies to link all this metadata. Using these ontologies, we can construct complete timelines of archeaological sites or objects, to facilitate searching and overview.
Future developments that are possible, are mobile uploading of archaeological images while excavating and even 3D reconstruction of sites using image recognition and stitching. The possibilities are endless and we are excited to continue development on this project.