DCHCTC2020: Data Analytics for Cultural Heritage: Current Trends and Concepts |
Submission link | https://easychair.org/conferences/?conf=dchctc2020 |
Abstract registration deadline | April 15, 2020 |
Submission deadline | May 15, 2020 |
Call for Book Chapters
Data Analytics for Cultural Heritage: Current Trends and Concepts
Editors:
Abdelaziz Bouras 1, Abdelhak Belhi 1,2, Abdulaziz Khalid Al-Ali 1, Abdul Hamid Sadka 3
- College of Engineering, Qatar University, Qatar
- DISP Laboratory, Université Lumière Lyon 2, Lyon, France
- Brunel University, London, United Kingdom
Introduction
Art and culture are some of the most reputable history transfer mediums through civilizations and generations. Cultural objects are distinguished by their higher value and attractiveness as they hold a lot of cultural and historical information. The physical preservation of cultural assets was known to be the only tool to conserve these objects for the long term. This process is reported to take a considerable amount of time and tends to be often costly. However, since the emergence of digital technologies, and thanks to their reliability and continuously dropping costs, the digital preservation of cultural objects is continuously catching the eyes of heritage organizations and is studied as an efficient and reliable alternative to the physical preservation. Cultural institutions such as museums, galleries, and heritage management organizations are currently investing a lot of efforts and resources to digitize and preserve their collections using cutting edge acquisition technologies. This process was often reported to be successful as we started to see multiple initiatives such as virtual museum tours, high-quality replicas of cultural objects, digital enrichment, linked data, etc. More recently, and with the recent breakthroughs in the AI domain, new techniques have been developed and aim at enriching the acquired data using artificial intelligence. In the past, cultural data enrichment was only possible using semantic tools or manual annotation which did not fully leverage the hidden information that can be extracted using AI technologies. Nowadays, artificial intelligence techniques for classification and content generation are being studied by multiple research groups around the world and thanks to the abundance of cultural data, some new challenges were presented to researchers to make the assets digital preservation more effective.
Throughout this book, we mainly consider the challenges related to the improvement of the data acquisition, data enrichment and data management processes in the cultural heritage data lifecycle pipeline using advanced artificial intelligence and machine learning technologies with an emphasis on recent applications related to deep learning for visual recognition, generative models, natural language processing, super resolution, etc.
Book Scope
In light of the recent advances and techniques in the cultural domain using artificial intelligence, the book aims at addressing new and current challenges related to the effective implementation of AI technologies in the cultural context. The book chapters are mostly related to the application of AI to the cultural heritage digitization process aiming at empowering the value of the digitized assets through advanced artificial intelligence techniques. We particularly focus on improvements to the data acquisition stage as well as the data enrichment and curation stages using advanced artificial intelligence techniques and tools.
For this book, we consider the following focus areas in the cultural heritage domain:
- Data acquisition
- Data enrichment
- Data management
- Data preservation
Academics, researchers, entrepreneurs and professionals are invited to contribute with book chapter(s) on the following:
“Data Analytics for Cultural Heritage: Current Trends and Concepts”
Authors interested in contributing with a chapter to the book should consider submitting an extended structed abstract. A template for structured abstracts is provided in the Appendix at the end of this Call for Chapters. We encourage authors to review the ten themes established for the book (see below) and indicate to which themes they intend to contribute.
Contact Information
For inquiries, please contact the editors through ceproqha@gmail.com
Timeline
Two-page Structured Abstract (see Appendix) Submission Deadline: 15th April 2020
Notification of Acceptance (Abstracts): 25th April 2020
Full chapter submission: 15th May2020
Review Results: 30th May 2020
Revised Chapter Submission: 10th June 2020
Final Acceptance: 15th June 2020
Deadline for sending Chapters to Springer: 30th June 2020
Submissions
Please use easychair to submit your chapters by the proposed deadlines above.
https://easychair.org/conferences/?conf=dchctc2020
Themes
Proposals should address one or more of the following themes within the “Cultural heritage and artificial intelligence” context.
Topic List (not limited to):
- Cultural data categorization
- Cultural heritage datasets
- Historical manuscript analysis
- Cultural repository analytics
- Cultural image inpainting and completion
- Cultural image super resolution and visual curation
- Cultural object marching and link retrieval
- Natural language processing in the cultural and historical contexts
- Cultural ontology learning
- Data analytics applications for attractiveness and targeted advertising in cultural heritage
Review Process
All submissions will be subject to a peer-review process. Extended abstracts will be reviewed by the editors; Full chapters will be reviewed by TWO international experts in the field.
Publisher
Springer
Author Submission Guidelines
Authors may review the Information for Authors of Springer Computer Science Proceedings following this link
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
Please note that:
- We accept files only .pdf/.doc/.docx files for submission
- Chapters must be in English and not more than 20 pages in length.
- Authors are required to ensure accuracy of quotations, citations, diagrams, maps, and tables.
- Figures and tables need to be placed where they are to appear in the text and must be clear and easy to view.
- Papers must follow the springer LNCS format available to download following this link :
ftp://ftp.springernature.com/cs-proceeding/llncs/word/splnproc1703.zip
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Appendix: Template for Structured Abstract Submission
LENGTH & STRUCTURE
Please limit structured abstracts to two pages (about 1000 words) and please include the sections described below replacing the instructions with your text.
Title of the Book Chapter
First Author Name (Firstname Last name), Second Author Namea, and etc b.
First Author Affiliation, Second Author Affiliation (if different)a , Subsequent Author Affiliationb
Corresponding Author Email:
BACKGROUND & PURPOSE
Please state here a background of the proposed chapter, for instance, is it a case study, a research work, a visionary model, etc. Please also inform about the chapter context, brief literature profile, motivation, and emphasis. Please state what are your research questions, or what is the purpose of your thesis, model, innovation, etc. Please include any other information you may also consider relevant.
DESIGN/METHOD/APPROACH
If empirical study or case, please include brief information of the developed research methods, what type of data were collected, and how data collection was conducted. If non-empirical chapter (e.g. visionary, debate oriented, proposed model of no empirical background, etc.), please support with a brief description of the approach you have proposed. Please include any other information you may consider relevant to this section.
RESULTS/ANTICIPATIONS
If empirical study or case, summarize the key results/outcomes. If non-empirical chapter, what are the anticipated results/outcomes of your research?
CONCLUSIONS
Please summarize the main conclusions of your study/research, or what would be the likely conclusion if non-empirical thesis.
REFERENCES
Please include references in alphabetical order using Stanford format for citing your references in the submitted abstract.
KEYWORDS
Include 3 to 5 relevant keywords.
SUBMISSION THEME
Please indicate under which theme(s) you are submitting your abstract. If none is relevant, please name a new one that you may consider more relevant.