«Data Analytics and Management in Data Intensive Domains» conference (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.
CALL FOR PAPERS
- General Information
- Conference topics
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. Official languages of the conference are English and Russian. 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.
- National Research University “Higher School of Economics”
- Federal Research Center "Computer Science and Control" of RAS (FRC CSC RAS)
- Moscow ACM SIGMOD Chapter
The XXV International Conference "Data Analytics and Management in Data Intensive Domains" (DAMDID/RCDL 2023) will be held during October 24-27, 2023 in Moscow at the Faculty of Computer Science, National Research University “Higher School of Economics”.
See you at: 11 Pokrovsky blvd, Moscow, Russia.
For participation at the conference the specialists from such DID as X-informatics (where X = astro, bio, chemo, geo, medicine, neuro, physics, etc.), social science, economy, finance, etc., as well as specialists in the areas of statistics, data mining, machine learning, informatics, data science, new technologies and IT, business, etc. are invited. Representatives of RCDL community are invited for submission of papers related to usual for RCDL topics, such as conceptual modeling, ontologies, data semantics, linguistics, NLP, multilingual text data, organization of new scientific data collection tutorials. Students and PhD students are welcome to participate at the conference with any kind of contribution related to the conference.
Categories of contributions to be submitted for publication and presentation
- regular papers reflecting original scientific results (from 10 to 15 pages);
- short papers (work in progress) (from 5 to 9 pages);
- posters (up to 4 pages);
- demos (up to 4 pages);
- tutorials (proposals should be submitted to the PC co-chairs).
For reviewing process papers of any category are submitted to the Program committee in digital form by the EasyChair system in PDF in strict conformance with the LNCS Word or Latex format.
Requirements to the final versions of accepted papers will be declared in accordance with suggested journal requirements after the final decision of the program committee.
Conferences DAMDID/RCDL hold face to face. Acceptance of a paper by the Program Committee assumes mandatory registration at the conference site (should be done before the camera ready submission deadline) and participation of at least one of the authors at the conference and personal presentation of the work. Remote participation exceptions should be negotiated with PC Co-Chairs.
The open list of topics proposed for submission is organized in form of the tracks presented in the list given below. It is important to note that such classification is valid only on the period of submission, reviewing and selection of papers. The structure of the conference program is defined by the Program committee relying on the selected papers and does not necessarily reflects the submission track structure. All tacks are open for submission of any categories of contribution including regular papers, short papers, posters, demos, tutorials.
Tracks for data analysis, problem solving, and experiment organization
- Problem statement and solving: urgent problem or phenomena required study in a specific domain or in a generalized way, thorough insight based on the nature, characteristics of the phenomenon and data available, approaches for organization of problem solving and methods selection, problem classification in various domains, process of problem solving and tools applied.
- Organization of experiments: survey of approaches for the organization of experimental research, scientific theory justification, experiment simulation, research cycles, robotization, infrastructures for experiment organization, reproducing of results, workflow metadefinition and reuse, verification of results, comparison of new results with those obtained earlier.
- Hypotheses and models as constituents of research experiments: methods and facilities for hypotheses generation and testing, construction of computerized models, models as a mean for theory and hypothesis verification, cognitive modeling paradigm, experience of creation of predictive models in research.
- Advanced data intensive analysis methods and procedures: state of the art in methods of statistics, data mining, machine learning, multivariate analysis, evaluation of methods generality and specialization, orientation of methods on specific domains and kinds of data, classification of methods, systematization of experience of methods application for problem solving, cognitive analytics for data-driven decision making, information visualization and exploratory analysis, meta-analysis methods, Big Data analytics efficiency and scalability, new data analysis methods development.
- Conceptual modeling: formalization of semantics of the subject domains, conceptual specification of problems and evolution of ontologies in specific domains, experience of applying of various models and tools for ontology support, semantic annotation for concept formation, progress of ontological modeling, ontological models use for database schema specification, independence of conceptual specification of data, abstract specification of algorithms and workflows in the conceptual models, semantic interoperability of programs.
- Research support in data infrastructures, data intensive use cases: functions and architectures of facilities for research support (virtual laboratories/observatories, data centers), cross-infrastructure interoperability and data sharing between interdisciplinary researches, data intensive use cases for research data infrastructures, experience of use case implementation.
Tracks for data management
- Methods, tools and infrastructures for data acquisition and storage: advanced projects, experience of data acquisition and storage in long-living projects, comparative analysis of the projects, project surveys, facilities and approaches for data collecting and storage, specificity of semantics, structure and characteristics of data (including streaming data), data representation, metadata organization, data quality, data provenance (including taking them from the literature), data cleansing, problems of Big Data storage.
- Data integration: methods and tools for entity resolution and fusion in the Big Data infrastructures, unification of various data models (such as NoSQL, graph-based, RDF-based, array-based models), canonical data models and their synthesis, schema and ontology matching and mapping, methods and tools for virtual data integration, application-driven subject mediators, semantic integration of data, data warehouses, ETL process support, multidimensional data models, data integration in hybrid infrastructures supporting structured, semi-structured and non-structured data, infrastructures of data integration systems, application of data integration facilities in specific domains.
- Information extraction from observational data: issues of extracting the most complete and up-to-date information from data in astronomy, spectroscopy, material science, medicine, etc.; application of data analysis methods to classify objects and search for anomalies
- Information extraction from texts: identification and extraction of structured information from the texts, declarative languages and methods for information extraction, linguistic methods, NLP, multilingual textual data, instruments for textual analysis.
- Research data infrastructures and their applications: various data infrastructures, based on data and compute-intensive platforms (such as clouds and grids, distributed clusters, supercomputers, parallel database machines, etc.), new models for data intensive programming in such infrastructures and Big data platforms, metadata and modeling in data infrastructures, virtualization based technologies, evaluation of performance of data infrastructures, scalability issues.
- Semantic Web role in DID: languages, tools, and methodologies for representing and managing data, semantics and reasoning on the Web, semantic interoperability and cross identification of the Semantic Web resources, spatio-temporal Semantic Web data and ontologies, harvesting of Semantic Web data from diverse data collections, Web data quality and provenance, multidialect architectures for declarative conceptual specification and problem solving over heterogeneous collections of data, application of Semantic Web facilities for problem solving, linked open data.
Conference Publications Overview
Soon after the conference post-proceedings volumes will be submitted to the Lobachevskii Journal of Mathematics, to the Pattern Recognition and Image Analysis, and to the Automation and Remote Control 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 journals like Systems and Means of Informatics, Information Technologies and Computing Systems , or Artificial Intelligence and Decision Making for indexing the papers in RSCI.
Previous DAMDID proceedings in Springer's Communications in Computer and Information Science (CCIS) 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/. All mentioned proceedings are indexed in Scopus.
Proceedings of 2022 are in press as special issues of the Lobachevskii Journal of Mathematics and the Pattern Recognition and Image Analysis; supplementary proceedings are in press as a special issue of the Proceedings of the Institute for Systems Analysis.
- Program Committee
- Organizing Committee
- Coordinating Committee
- Sergey Kuznetsov, NRU Higher School of Economics, Russia
- Dmitry Ignatov, NRU Higher School of Economics, Russia
- Sergey Stupnikov, FRC “Computer Science and Control”, RAS, Russia
- Jaume Baixeries, Universitat Politecnica de Catalunya
- Sergey Stupnikov, Institute of Informatics Problems, Russian Academy of Sciences
- Anastasia Mezentseva, A.P. Ershov Institute of Informatics Systems, Siberian Branch, Russian Academy of Sciences, Novosibirsk
- Valery Sokolov, Yaroslavl State University
- Vladimir, Serebryakov Computing Centre of the RAS
- Yury Gapanyuk, Bauman Moscow State Technical University
- Anna Glazkova, University of Tyumen
- Manuel Mazzara, Innopolis University
- Alexander Veretennikov, Ural Federal University
- Dmitry Borisenkov, Voronezh State University
- Михаил Леонидович, Цымблер, South Ural State University
- Dmitry Kovalev, IPI RAN
- Alexey A. Mitsyuk, HSE
- Francesco Mercuri, DAIMON Team - CNR-ISMN
- Ildar Baimuratov, ITMO University
- Sergey Makhortov, Voronezh State University
- George Chernishev, SPbU
- Yury Zagorulko, A.P. Ershov Institute of Informatics Systems, Russian Academy of Sciences
- Nikolay Skvortsov, FRC CSC RAS
- Fail Gafarov, Kazan Federal University
- Ilya Sochenkov, Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
- Eugene Ilyushin, Lomonosov Moscow State University
- Jaume Baixeries, Universitat Politecnica de Catalunya
- Dmitry Ignatov, National Research University Higher School of Economics
- Dmitry Namiot, MSU
- Natalia Loukachevitch, Research Computing Center of Moscow State University
- Pavel Velikhov, ISP RAS
- Alexei Pozanenko, Space Research Institute
- Nadezhda Kiselyova, A.A. Baikov Institute of Metallurgy and Materials Science of RAS
- Roman Samarev, Bauman Moscow State Technical University
- Alexander Afanasyev, IITP RAS
- Anna Grinevich, Institute of Philology of Siberian Branch of Russian Academy of Science
- Dana Kovaleva, Institute of Astronomy, Russian Academy of Sciences
- Victor Zakharov, IPI RAN
- Alexander Fazliev, Institute of Atmospheric Optics
- V.E.Zuev, Institute of Atmospheric Optics
- Manfred Sneps-Sneppe, Ventspils University of Applied Sciences
- Sergej Znamenskij, Ailamazyan Pereslavl University
- Sergei Kuznetsov, Ivannikov Institute for System Programming of the RAS
- Oleg Malkov, Institute of Astronomy, Moscow
- Vitaliy Kim, HSE
- Boris Dobrov, Recearch Computing Center of Moscow State Univ.
- Vasily Bunakov, STFC
- Dmitry Nikitenko, Moscow State University
- Alexander Sychev, Voronezh State University
- Igor Fiodorov, Plekhanov Russian University of Economics (PRUE)
- Dmitrii Deviatkin, Institute for Systems Analysis
- Ivan Luković, University of Belgrade, Faculty of Organizational Sciences
- Irina Filozova, JINR
- Mikhail Melnikov, Federal Research Center of Fundamental and Translational Medicine
- Aleksei Romanov, ITMO University
- Bernhard Thalheim, Christian-Albrechts-Universität zu Kiel
- Mirjana Ivanovic, University of Novi Sad, Faculty of Sciences, Department of Mathematics and Informatics
- Archil Maysuradze, Lomonosov Moscow State University
- Panagote Pardalos, University of Florida
- Alexander, Elizarov Kazan Federal University
- Jeyhun Karimov ,Technical University of Berlin
- Evgeny Lipachev, Kazan Federal University
- Nikolay Kolchanov, academician RAS, Institute of Cytology and Genetics, SB RAS, Novosibirsk
- Igor Sokolov, academician RAS, FRC “Computer Science and Control” of RAS, Russia
- Sergey Stupnikov, FRC “Computer Science and Control” of RAS, Russia
- Arkady Avramenko – Pushchino Radio Astronomy Observatory, RAS, Russia
- Pavel Braslavsky – Ural Federal University, SKB Kontur, Russia
- Vasily Bunakov – Science and Technology Facilities Council, Harwell, Oxfordshire, UK
- Alexander Elizarov – Kazan (Volga Region) Federal University, Russia
- Alexander Fazliev – Institute of Atmospheric Optics, RAS, Siberian Branch, Russia
- Alexei Klimentov - Brookhaven National Laboratory, USA
- Mikhail Kogalovsky – Market Economy Institute, RAS, Russia
- Vladimir Korenkov – JINR, Dubna, Russia
- Sergey Kuznetsov – Institute for System Programming, RAS, Russia
- Vladimir Litvine – Evogh Inc., California, USA
- Archil Maysuradze – Moscow State University, Russia
- Oleg Malkov – Institute of Astronomy, RAS, Russia
- Alexander Marchuk – Institute of Informatics Systems, RAS, Siberian Branch, Russia
- Igor Nekrestjanov – Verizon Corporation, USA
- Boris Novikov – St.-Petersburg State University, Russia
- Nikolay Podkolodny – ICaG, SB RAS, Novosibirsk, Russia
- Aleksey Pozanenko – Space Research Institute, RAS, Russia
- Vladimir Serebryakov – Computing Center of RAS, Russia
- Yury Smetanin – Russian Foundation for Basic Research, Moscow
- Vladimir Smirnov – Yaroslavl State University, Russia
- Sergey Stupnikov – Federal Research Center “Computer Science and Control” of RAS
- Bernhard Thalheim - Kiel University
- Konstantin Vorontsov – Moscow State University, Russia
- Viacheslav Wolfengagen – National Research Nuclear University "MEPhI", Russia
- Victor Zakharov – Federal Research Center “Computer Science and Control” of RAS, Russia
Contact person: Dmitry Ignatov
✉ Email: email@example.com
11 Pokrovsky blvd, Moscow, Russia
🚇 Kurskaya, Chistye Prudy