In the field of Digital Cultural Heritage the data produced and used will include the following 

 

 

Modules and components for the VI-SEEM scientific application environment

for individual operations, and docker containers for every module that can be shared and/or reused, e.g., 3D model cleaning, generating and streaming a 3D model, Interactive 3D Museum tours and web UI creation. Also OCR module, and Databases of complex datasets, e.g., handwritten Arabic, Hebrew and Karamanlidika texts - for searching and identifying of phonetic varieties of the indexed lexemes, as well as the finding of grammatical and formational suffixes..

 

Documentation and analysis datasets of structures, works of art and artefacts.

IWeb UI for new tools for modelling of geoelectrical tomographic data, subsurface reconstruction and imaging; datasets of CH artefacts; regional datasets like MEGA Jordan GPS/ geo-referenced data.

3D visualization and analysis

This category involves online visualization viewers for x3D, 3D pdf of image-based 3D reconstructions (Structure-from-Motion/photogrammetric techniques) and RTi ptm files, as well as MS Word and pdf files.

Metadata

of the Digital Cultural Heritage community will be mostly freely exchangeable and open, except from a few cases of copyrighted material - in particular ancient coins, rare books and unpublished Ptolemaic inscriptions. The VI-SEEM Cultural Heritage metadata shall follow the CIDOC-CRM RDF (Dioptra), ARC2 triple store, ISBD –M, and UNIMARC (BVL) standards, respectively. Metadata will mostly be generated from the operation of Digital Libraries, the application of semantic referencing and annotation, users' annotations of digitized artifacts and reconstructed historical objects, as well as from the publication of databases and use of OCR tools. Metadata standardization, e.g., Dublin Core and derived/related standards, XML, is important as it will allow for their mapping, e.g., Open CV and MINT, and interoperability across platforms, e.g., Spark SQL, ASCII.

Available Pre-Processed data

Electronic Corpus of Karamanlidika Texts

Access dataset Access dataset through Clowder

Source: ELKA - Karamanlidika Texts
Charge: Free
Processing Level: Processed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Matthias Kappler
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
 

Access dataset Access dataset through Clowder

Source: BVL - Banatica Database (200 Digitized Books)
Charge: Free
Processing Level: Processed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Delia Pârșan
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Three-dimensional (3-D) inversion of surface Electrical Resistivity Tomography (ERT) data in order to automatically determine a 3-D resistivity subsurface model. The collection contains five datasets.

Access datagroup

Source: 3DINV
Charge: Free
Processing Level: Unprocessed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Angelos Hliaoutakis
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Note: To access this dataset you need to have authorised access to the data collection.

The Historical Arabic Documents Dataset for Recognition Systems
Annotation on sub-word level of five books written by different writers from the years 1088-1451.

Access datagroup

Source: MANUSCRIPT
Charge: Free
Processing Level: Unprocessed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Jihad El-Sana
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Note: To access this dataset you need to have authorised access to the data collection.

CNN Features for Remote Sensing Image Classification
Tools and resources for remote sensing image classification using convolutional neural networks (convnets).
Collection SAT CNN Models contains code and pretrained convnet models for classification of satellite images. The convnets are trained on publicly available SAT-4 and SAT-6 datasets of satellite images (http://csc.lsu.edu/~saikat/deepsat/). Collection contains the following datasets:
- SAT-4 Models - CNN models trained on SAT-4 dataset
- SAT-6 Models - CNN models trained on SAT-6 dataset
- Tools & Results - code for convnet training and image classification, conference paper and presentation

Access dataset

Source: CNN Features for Remote Sensing Image Classification
Charge: Free
Processing Level: Unprocessed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Vladimir Risojević
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. 

Available Documentation and analysis data

VISTA - Bibliotheca Alexandrina
Popularize the museum experience by adding many ways to simplify and present archaeological and historical data. By utilizing advance programming and graphics techniques, we aim to make a tool that complements and enriches the real museum, substitutes for the inability to visit it, adds new layers and means of storytelling, connects multiple museums worldwide, and that can be used remotely by anyone in the world.
The datagroup consists of one dataset, two documents and two presentations.

Access datagroup

Source: VISTA
Charge: Free
Processing Level: Unprocessed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Mohammed Elfarargy
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Available 3D visualization and analysis data

Fourier Transform Infrared Spectra of two sets of samples: 1. Wall paintings 2. Marble Sculpture Scientific Contact: Maram Na'es, Technical University Berlin, Department of Optics and Atomic Physics/ and Synchrotron-light for Experimental Science and Applications in the Middle East (SESAME).

Access datagroup

Source: PETRA
Charge: Free
Processing Level: Unprocessed Data
Use Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)
Contact: Maram Na'es
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.