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DAMDID 2024 : 26th International Conference on Data Analytics and Management in Data Intensive Domains

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Link: https://damdid2024.frccsc.ru/
 
When Oct 22, 2024 - Oct 25, 2024
Where Nizhny Novgorod, Russia
Submission Deadline May 13, 2024
Notification Due Sep 2, 2024
Final Version Due Sep 16, 2024
Categories    data science   data management   data integration   semantic web
 

Call For Papers

The 26th International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID) is planned as a multidisciplinary forum of researchers and practitioners from various domains of science and research promoting cooperation and exchange of ideas in the area of data analysis and management in data intensive domains. Approaches to data analysis and management being developed in specific data intensive domains of X-informatics (such as X = astro, bio, chemo, geo, medicine, neuro, physics, etc.), social sciences, as well as in various branches of informatics, industry, new technologies, finance and business are expected to contribute to the conference content.

DAMDID conference was formed in 2015 as a result of transformation of the RCDL conference («Digital libraries: advanced methods and technologies, digital collections», http://rcdl.ru) with an intention to create a forum reflecting the urgent challenges of data organization, exploration and analysis in various data intensive domains (DID). The transformation was provided so that the continuity with RCDL has been preserved by the transformed conference as well as the RCDL community formed during the sixteen years of its successful work also has been preserved.

Exponential growth of data practically in all activity areas and consolidating role to be played by informatics and IT for the development of methods and facilities for data analysis and management in various data intensive domains (DID), study of experience of such methods application and stimulating of their advancement serve as a motivation for this conference organization

Main objective of this conference is to promote the acceleration of researches, improvement of their efficiency (quality and visibility of results, competitive ability) at the expense of the enhancement of methods and facilities for data analysis and management in DID. It is expected that the mutual complementarity of approaches in interdisciplinary DID will contribute to the creation of the corporate culture generalizing methods for data analysis and information systems development applicable in diverse DID.

The conference structure includes plenary invited talks and tutorials presented by the leading researchers, regular sessions containing regular and short presentations of the research results obtained in various conference tracks, as well as demo/poster sessions. The official language of the conference is English. In frame of the conference the PhD Workshop is planned that is oriented on the young researchers. Co-located with the conference the satellite events are also planned including workshops (open and by invitation) and invited sessions.

The selection of papers for the Conference is made according to the results of the independent reviewing of a submission by three members of the Program Committee. The Program Committee can accept work for presentation as a regular paper, short paper, poster or demo.

The open list of topics proposed for submission is organized in form of the tracks presented in the list given below.

Tracks for data analysis, problem solving, experiment organization

Problem statement and solving
Organization of experiments
Hypotheses and models as constituents of research experiments
Advanced data intensive analysis methods and procedures
Conceptual modeling
Research support in data infrastructures, data intensive use cases

Tracks for data management

Methods, tools and infrastructures for data acquisition and storage
Data integration
Information extraction from observational data in astronomy, spectroscopy, material science, medicine, etc.
Information extraction from texts
Research data infrastructures and their applications
Semantic Web

The XXVI International Conference “Data Analytics and Management in Data Intensive Domains” (DAMDID/RCDL 2024) will be held during 22-25 October 2024 in Nizhny Novgorod at the Faculty of Informatics, Mathematics, and Computer Science, HSE University, Nizhny Novgorod, Bolshaya Pecherskaya street, 25/12.

Conference post-proceedings consist of Conference Track proceedings (full papers and some high-quality short papers in English) to be submitted to Springer's Communications in Computer and Information Science (CCIS, http://www.springer.com/series/7899) and Journal Track proceedings (limited topics) to be submitted to Lobachevskii Journal of Mathematics (https://www.springer.com/journal/12202), to the Pattern Recognition and Image Analysis (https://www.springer.com/journal/11493), and to the Automation and Remote Control (https://www.springer.com/journal/10513) for the sake of better visibility of the conference publications by the international scientific community, as well as for indexing the papers in Scopus and Web of Science. Supplementary volume will be submitted to scientific journal Systems and Means of Informatics (http://www.ipiran.ru/english/journal_Systems/index.asp) for indexing the papers in RSCI.

Previous DAMDID proceedings in Springer's Communications in Computer and Information Science (CCIS, http://www.springer.com/series/7899) for 2016-2021 are available at https://link.springer.com/conference/damdid. Previous proceedings in CEUR for 2011-2021 are available at https://ceur-ws.org/. Proceedings of 2022 are published as special issues of the Lobachevskii Journal of Mathematics (https://link.springer.com/journal/12202/volumes-and-issues/44-1) and the Pattern Recognition and Image Analysis (https://link.springer.com/journal/11493/volumes-and-issues/33-2); supplementary proceedings are published as a special issue of the Proceedings of the Institute for Systems Analysis (https://isa.ru/proceedings/index.php?option=com_content&view=article&id=1226&Itemid=&lang=en)

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