COARCH'19: 3rd Workshop On Computing Techniques For Spatio-Temporal Data in Archaeology And Cultural Heritage Regensburg Regensburg, Germany, September 10, 2019 |
Conference website | http://coarch19.di.univr.it/ |
Submission link | https://easychair.org/conferences/?conf=coarch19 |
Submission deadline | June 1, 2019 |
Archaeological data, and more in general cultural heritage information, are characterized by both spatial and temporal dimensions that are often related to each other and are of particular interest for supporting the interpretation process through which new knowledge can be achieved about ancient times.
For this reason, several research works proposed attempts to develop new information management techniques, some of them directly inherit from geographical information science. However, cultural heritage and archaeology still require a tailored support to:
- the collection of spatio-temporal data and their effective representation for enhancing interoperability, especially with the rise of 3D acquisition techniques that involves big data characteristics;
- the processing of raw data in order to identify artifacts and define their allocation in space and time, in relation with ontological developments;
- the reconstruction of ancient structures (buildings, walls, castle, etc.) or their temporal evolution, based on deep learning process allowing automatic reconstruction, segmentation, complex objects identification;
- the integrated access and querying of the collected data in different formats, structures, data models;
- the development of tailored representation methodologies or spatio-temporal archaeological information.
The aim of the workshop is to bring together researches of the fields of spatial information science, knowledge representation and knowledge discovery to share their research results in order to draw the new incoming challenges in terms of archaeological and cultural heritage spatial information management applications.
Submission Guidelines
Submissions of high quality papers describing research results or on-going work are solicited. Submitted papers should contain original, previously unpublished content, should be written in English, and must not be simultaneously submitted for publication elsewhere. Submitted papers will be refereed by at least three reviewers for quality, correctness, originality, and relevance. Accepted papers will be presented at the workshop and included in the proceedings.
List of Topics
This exploratory workshop deals with a hot topic in term of spatio-temporal information management. Organizers will pay a particular attention to presentation with working prototypes and live results presentation.
Knowledge representation
- Modeling of spatio-temporal data in archaeology and cultural heritage
- Techniques for supporting interoperability of spatio-temporal data
- 3D digital artifact capture, representation and manipulation
- Workflow design for supporting the archaeological interpretation process
Knowledge discovery
- Analytic tools to assist scholars’ research on archaeological data
- Tools for reconstruction and processing of spatio-temporal evolution
- Spatial temporal data mining on spatio-temporal data in archaeology
- Machine learning techniques applied to archaeological data
Committees
Program Committee
- Alberto Belussi, University of Verona, Italy
- Sara Migliorini, University of Verona, Italy
- Roland Billen, Geomatics Unite ULiège, Belgium
- Pierre Hallot, Cultural Heritage ULiège, Belgium
Organizing committee
- Alberto Belussi, University of Verona, Italy
- Sara Migliorini, University of Verona, Italy
- Roland Billen, Geomatics Unite ULiège, Belgium
- Pierre Hallot, Cultural Heritage ULiège, Belgium
Publication
Submitted papers will be refereed by at least three reviewers for quality, correctness, originality, and relevance. Accepted papers will be presented at the workshop and included in the proceedings.
Venue
The workshop will be held at Regensburg, Germany, on September 10, 2019 in conjunction with COSIT 2019 (14th International Conference on Spatial Information Theory).