About the conference

Make history
General info
Scope of the conference
The CODATA Conference was held in the Russian Federation for the first time. It rought together more than 150 participants from 35 countries. Among the participants were leading scientists, specialists in BIG DATA and modern methods of data processing, image recognition and in-telligent data analysis, data collection engineers and technologists. International multidisciplinary scientific dialogue between representatives of various fields of knowledge was held under the aegis of promoting of Open data principles and FAIR (Findable, Accessible, Interoperable and Re-usable) data.
The conference covered a wide range of issues related to data sciences, including the collection and processing of large amounts of data, the use of methods of system analysis, machine learn-ing and algorithms of artificial intelligence. During four days of the conference, more than 160 scientific presentations were shown at 25 scientific sessions, several business meetings and workshops were held.

The conference has been supported by the Russian Science Foundation
(RSF Project 15-17-30020)
Smart Cities
Data Platforms for Earth Observation and Interoperability
Data Policy, FAIR Data, Legal Issues and the Limits of Open Data
Data Analysis and Big Data - Health
Open Data and Education
Geological data-driven science of the Arctic
During the Arctic Workshop, extensive discussion of new geological data is planned, including geophysical, stratigraphic-paleontological, isotope-geochronological, tectonic, structural-geological studies of the Arctic and the Arctic Ocean.

The discussion of these problems and directions will promote the growth of mutual understanding between geologists of different countries and various geological schools in developing common position on the tectonic structure of this complex and inaccessible region of the planet.

The workshop will stimulate the exchange of information and technologies between geological surveys and national academies of sciences and will become the driving force for the development of Earth sciences, including the development of our knowledge gained from the international project “Atlas of geological maps of the Circumpolar Arctic in 1: 5 M”.
A Data-Driven Approach to Urban Health and Well-Being
By 2050, almost 70% of the population will live in urban areas. Urbanisation has both positive and negative impacts on human health. In order to understand the health consequences of government policies in cities undergoing rapid expansion, planners, policy makers and researchers are using health indicators and Health Impact Assessment (HIA) tools. Health indicators and HIA provide a data-driven, evidence-based approach to urban planning and policy making - to ensure policy and planning decisions will enhance positive impacts on health and minimize negative impacts.

This transdisciplinary session will involve a set of practice papers that describe tools and methodologies which focus on:

- conceptual models for defining and relating human health metrics with environmental health in complex, dynamic urban systems;

- the integration of multiple datasets to generate indicators that assess health and related aspects of urban regions, such as transport, housing, food, water and environment (e.g., air quality);

- use of indicator data and Health Impact Assessment tools to identify and address health issues and inequalities arising from urbanization and urban policies;

- data-driven and systems approaches to monitor urban health indicators and relate them to policy, environmental and demographic changes over time and place;

- simulating, modelling and predicting the impact of urban change and urban policies on the health and wellbeing of its residents.

Invited speakers will describe exemplar case studies from China, the UK, Europe, Latin America and Australia. These papers will demonstrate how researchers are working to assist city planners and policy makers to make better urban planning decisions which will protect and promote urban health and well-being both now and in the future.
Data mining aimed at seismic hazard and risk assessment and earthquake prediction
Reducing the impact of natural and man-caused catastrophic events is a complex scientific and technical problem, which is of great social and economic importance. Its urgency is continuously increasing due to rising population density, anthropogenic impact on natural environment, development of environmentally hazardous industries, and expansion of mining production and of oil and gas extraction. The session is devoted to approaches that are aimed at seismic hazard and risk assessment and earthquake prediction and to the data that are needed for these purposes.

Results of creation and development of the phenomenological, system, geoinformational approaches to the multivariate seismic hazard assessment based on artificial intellect algorithms will be presented as well as carrying out of the seismic hazard assessment for specific tectonically active regions by means of these approaches and representation of the results using GIS technologies.

Reliable methodologies of neo-deterministic seismic hazard analysis and intermediate-term middle- to narrow-range earthquake prediction algorithms tested in real-time applications over the last decades will be considered.

Among other questions to be considered there are the integrated research on earthquake disaster risk, the scientific and educational aspects of disaster risk reduction, new approaches to seismic hazard assessment, observing and modeling capabilities to reduce uncertainties in hazard assessment, a contribution of hazard and vulnerability to earthquake risk, scientific, economic and political factors as well as the factors of awareness, preparedness and risk communication, which brought about the humanitarian tragedies of the early XXI century, and trans-disciplinary system approaches to disaster risk research and assessment.
Modern strategies for data collection and analysis for the better understanding of the Earth system
In the past decades, the demand for information about the planet in which we live is driving the creation of new highly capable observing and collection systems. Environmental observations are critical for forecasting weather and climate, monitoring geophysical fields, volcanoes, seismicity, tsunamis, etc. and in assessing the recovery from disasters. In this scenario, Earth observation technologies are developing rapidly to collect data from diversified locations over shorter periods of time, and in turn the datasets generated can be combined and analyzed to gain new scientific insights. How to create an integrated system for Earth and environmental observation, collection and analysis in order to manage the increasing volume of data allowing easy access by the research and civil community? Each of the topic areas requires a range of measurements derived from a variety of platforms including satellite, airborne and in situ. Merging observed data with geospatial analysis allows the generation of better knowledge of natural processes and risk management.
Many examples of Earth and environmental measurements have improved the way we look at the Earth’s system, both below ground and above. Particularly, aerial photogrammetry is a useful tool for area-wide mapping and monitoring of permafrost geometry, thickness changes and surface creep; satellite radar interferometry becomes an important tool for determining ice-flow velocity. ESA's Swarm 3-satellite mission provides unprecedented quality of the Earth's magnetic and electric field observations, which enable high-precision and high-resolution modelling of the interior and atmospheric electromagnetic processes, as well as ocean circulation patterns that affect climate and weather. The ever-improving spatial and temporal coverage of geodetic images motivates better quantification of the sources of error in those data sets and helps with the rigorous characterization and resolution of the deformation sources in space and time.
The large volume of available observations presents a large number of challenges, including the characterization and treatment of noise and desired signal in the data and practical considerations of how to minimize the computational cost of examining such large data sets. The session will provide modern insights into creation of integrated systems for Earth and environmental observations, their collection and analysis in order to manage efficiently the increasing data volumes and provide easy access to the research and civil communities. The session will also consider the state-of-the-art and perspectives in data science relevant to Earth observations and environmental research.

The session is organized by the Union Commission for Data and Information (UCDI) established by the IUGG.
Historical Disaster Data Management and Data Publishing
Data has been regarded as one of the most important resources for disaster reduction, such as the quick response maps from observed data, the disaster loss information from multidisciplinary data, the knowledge and decision from mass information, the advice to post-disaster construction from stakeholders and the early warning and risk research from data simulation. The multidisciplinary data to record the event of certain disaster is the historical documents for future disaster research, as the medical examination data for illness of human beings. However, lots of such historical dataset for certain natural disaster events have been lost after decades, even these events impacted and heat all heart around the world for their damage.

In recent years, there was a surge in the volume of the historical disaster collection, preservation and data sharing. More and more such datasets can be discoverer and accessible. But few of disaster datasets are published to make them trust, copyright-clear, and cited. CODATA Task Group of Linked Open Data for Global Disaster Risk Research is working on promoting the data publishing on event-oriented disaster datasets, as an apporach to manage the diaster realted data.

This proposed session is co-hosted and supported by CODATA LODGD Task Group,IRDR Data Working Group,TWAS-CAS SDIM and GEO.
Institutional RDM services
Research Data Management [RDM] is increasingly important in institutions as data is growing in unprecedented volumes. Furthermore, good research practice, the tangible benefits of data reuse, re-analysis and large scale analysis or integration in meta-studies, all mean that research institutions need to improve their ability to manage and curate digital data. Reflecting these drivers a growing number of funders and scholarly journals have developed research data policies. Consensus is building that research data should be ‘open by default’ and FAIR.

Although data is increasingly viewed as an important institutional asset, the challenges posed are significant. The data produced in research institutions is diverse in terms of domains, content, formats and encoding. Research data management presents major challenges at several stages in the data cycle such as data selection, curation, standards and representation, processing and services that need to be addressed. Institutional data can only be utilized effectively through well planned RDM services in institutions. There are several issues that need the attention of the research community in relation to RDM policy and guidance, support and sustenance, technology infrastructure and training. The objective of the session on Institutional RDM services is to bring together experts, researchers and practitioners who are active stakeholders to facilitate discussions on important initiatives, policy guidelines and other related issues in RDM services. It is the aim to attract attendance from institutes, libraries and initiatives that are involved in providing RDM services particularly to highlight the issues faced and successful practices in RDM services.
Earth observing systems and data for global energy, oil and gas extraction and carbon dioxide storage
The objective of this session is threefold:

To assess the range of natural gas (including oil) role in future global energy developments and potential carbon dioxide capture and storage needs.
To integrate data on energy perspectives including carbon dioxide storage possibilities with data on Earth observing systems including geomagnetism.
To discuss the role of advanced drilling techniques with geomagnetic steering in the context of global energy and climate change mitigation strategies.
Data and Disaster Risk Research
Session on Data and Disaster Risk Research. Leading with paper on Sendai from Virginia Murray then other papers on disaster risk.
Practice and Impact of Data Citation
Session on the practice and impact of data citation.
CODATA Constants and Mathematical Data Analysis
Session on CODATA Constants and Mathematical Data Analysis
A World Tour of Progress toward Open Data and Open Science
A Panel discussion will address the policies and national perspectives on Open Data and Open Science, and survey progress towards these objectives in a range of countries. The Science International Accord on Open Data in a Big Data World, laid out a set of principles and enabling practices in order that open data should advance science, particularly in major interdisciplinary research areas. Combined with the maxim that research data should be ‘open by default’ or ‘as open as possible, as closed as necessary’, the FAIR principles are gaining acceptance as a useful and effective summary of the attributes that allow data to be understood and analysed, that give data value. Building on previous formulations (OECD, Royal Society, G8 Ministers) the FAIR Principles are as follows:

Data should be Findable
Data should be Accessible
Data should be Interoperable
Data should be Re-usable.
The European Commission and the NIH have launched activities to guide and facilitate the implementation of these principles. Open science initiatives and open data policies are becoming more prevalent. It is timely then to review progress and the perspective of CODATA National Members.
Data Driven Knowledge-Based Systems for Basic and Applied Sciences: Combustion, Detonation, Nanotechnology, Renewable Energetics, etc
From the data to the Knowledge is the main topic of the session.

Nowadays a solution of many problems that could not be solved early hasbecome possible by means of Data Science. One of such problems is a creation ofnew sort of Knowledge-Based system (KBS). Under the new sort of KBS we mean thecalculation tool that: contains all relationships between all variables of theobject; allows to calculate the values of one part of variables through others;allows to solve direct and inverse problems; allows to predict thecharacteristics of an object that have not been investigated yet; allows topredict technology parameters to obtain an object with desired characteristics.An ensemble of multifactor quality, quantity and computational models are thebase of new sort of KBS.

The formulations of the problems of a creation of new sort of KBS, themethodology, methods, techniques, and tools for a creation of KBS will bediscussed on the session. The best practice and examples of KBS created invarious areas of basic and applied research of combustion, nanotechnology, MaterialsGenome, solar energetic, socio-economic systems, etc will be presented anddiscussed. Two analytical platforms “Deductor” and “PolyAnalyst”, that have alltools for creation KBS will be presented. We expect to have speakers on avariety of topics related to KBS creation. Preliminarily identified speakerswill address issues of the formulations of the problems of a creation of newsort of KB.

Inconclusion, the Motto: The Knowledge-Based System is a Goal and a Tool forBasic and Applied Research as well as prospects of joint research will bediscussed.

During the session we plan to demonstrate possibilities of the Data ScienceMethods application in the generalization of the connections between theexperimental variables of an object as well as in forecasting of “newexperimental results” without real experiments.

We believe that Data Science Methods will be considered as a powerful tool,which supports an interchange between experiment, computer simulation, andengineering calculation.
Big Data in Scientific and Commercial Sectors
As we enter this new era of MDM, where data is big data, an enhanced definition and expansion of Master Data value has emerged. Master Data has been primarily credited with assisting enterprises in denoting the proverbial single version of the truth.

Master Data with Big Data expands the data value enabling the ability to derive a more comprehensive understanding of this single version of truth by creating a profile based on any host of relevant external factors.

Existing solutions lack the features and capabilities to provide a complete set of end-to-end ‘New’ MDM service for Big Data given the changing requirements and data landscape.

New MDM solutions should combine traditional MDM capabilities with emerging Big Data models (contextual & analytical) to accommodate new requirements in the era of Big Data and Data Lakes, by leveraging Graph database, Blockchain, Artificial Intelligence and Machine Learning.

Papers in this category will address the different aspects of data management including but not limited to ingestion, data quality, integration, transformation, storage, processing, access, semantic representation, analytics, security and governance.
Great earthquakes and tsunamis in subduction zones
Subduction zones produce the largest earthquakes in the world. During the decade from mid-2004 to mid-2014 18 great earthquakes (with magnitude Mw > 8) occurred globally, compared to 71 from 1900 to mid-2004, yielding a short-term rate increase of 265% (Lay,2014). Coseismic slip of tens of meters can cause devasting shaking and tsunami, as recently demonstrated by the December 26, 2004, Mw=9.2 Sumatra earthquake and the March 11, 2011, Mw=9.0 Tohoku, Japan earthquake. The recent decade of intense great earthquake activity coincide with vastly expanded global network of seismometers, GPS stations, tsunami DART system, satellite interferometry InSAR and LandSAR, gravity measurements GRACE and GOCE, enabling new analyses of precursory, co-seismic and post-seismic processes near the subduction zones where most of the events occurred. Over the past decade space geodesy has revolutionized our view of crustal deformation between consecutive great earthquakes. The short time span (several years) of modern measurements necessitates comparative studies of subduction zones that are at different stages of the seismic deformation cycle (SDC). For each subduction zone high-quality modern geodetic observations provide a “snapshot” of its SDC evolution. It has become evident that these snapshots reflect a common SDC that includes the three main processes took place after each great earthquake: (1) continuing slip of the fault (so called “afterslip”); (2) viscoelastic relaxation of the earthquake-induced stress, and (3) relocking of the subduction fault. The great earthquake rupture typically extends for hundreds of kilometers along a single subducting plate. These ruptures often begin or end at structural boundaries within the overhanging plate that are associated with the subduction of prominent bathymetric features of the plunging plate. Convergent plate margins have a segmentation or block-like nature. (Mogi, 1969) illustrated with several examples from the circum-Pacific belt his finding that great earthquakes and their aftershock zones occur in non-overlapping units separated by structural discontinuities in the arc. The block-like structure of the front part of an overhanging plate has been demonstrated for the Kuril-Kamchatka, Aleutian, Peru-Chile, Japan, Solomon and other subduction zones. The understanding of separated frontal blocks within island-arc and active continental margins as main seismogenic elements associated with the sources of great earthquakes has led to the formulation of the mechanical keyboard model of the seismic deformation cycle (Lobkovsky, 1982). This session will foster broad discussion and stimulate joint effort to study the great earthquakes and tsunami occurring in subduction zones using the modern GPS observation in framework of keyboard model of deformation cycles of frontal seismogenic blocks of the island arcs and active continental margins.
Research data - a multi-dimensional peg in academic publishing’s square hole?
In order to manage, use and validate research data, several mental models of data have arisen across research communities in recent years. Whether those are the “Big Iron” (industrialised processes for producing and managing data) or the “data as a paper” method for validating, attributing and assigning credit, data can be pushed into a model that does not capture the full variety of behaviours and intricacies, but can provide useful shortcuts and prior experience with which to build new systems and communicate with stakeholders. All of these models are imperfect, but many are useful - the problems arise when one model is deemed to be superior, or more valuable than the others, thereby giving the perception that the datasets that don’t fit easily into that model are somehow inferior or flawed.

Data publication has been proposed as a method for validating, publicising and attributing research data, and has, in recent years, become more well known in the research community, especially given the proliferation of data journals. Not all datasets are suitable for publication in such a way, however, due to a combination of factors including (but not limited to) the long term or dynamic nature of the dataset, the confidentiality and privacy of the data source(s), and potentially the sheer size of the dataset. Yet researchers still want to be able to discover, understand and use these datasets, secure in the knowledge that quality control and verification of the data have been carried out. Similarly, researcher funders wish to ensure that Open Data and other data management mandates have been adhered to.

This session aims to discuss data publication from the point of view of new tools and services to make publishing data easier and more effective, as well as self-sustainable. But it also seeks to identify other models to not only promote data as a first class research output, providing the description, validation and attribution functions for data which are currently associated with academic journal publication of research results, but also to deal with the reproducibility crisis, and to protect the integrity of the scientific record.
Regional Collaboration for Data Science
At a Practice Papers session of “Regional Collaboration for Data Science”, the case studies for regional collaborations are presented by speakers with the aim of identifying the challenges in conducting Data Science through various levels of regional collaborations such as intra-domestic regions, bilateral nations, and much larger regions like the Pacific Rim.
Different from international collaborations, the regional collaborations on Data Science are considered much easier because they tend to share the common interest as well as the common strategies to tackle an issue to be solved in a given project. On the other hand, however, there are always some difficulties in keener competition due to similar interest and strategies in conducting data science. Although these possible difficulties may depend upon the area of research and developments (R&D) and a level of regional collaboration, it will be very useful if we can sort them out for identifying the challenges common or unique to regional collaborations for conducting Data Science.
In particular, the issues of Big Data as well as Small Data are very common among different projects in regional collaborations. Therefore, the database construction for Data Science will be of common practice for regional collaborations. However, these databases constructed through regional collaboration may be very specific for that region, and thereby it will be a significant problem on how the regional efforts can be coordinated with a larger-scaled international collaboration along with funding issues.
Moreover, AI (Artificial Intelligence) such as machine learning, text mining, and deep learning as well as IOT (Internet of Things) / IOE (Internet of Everything) have become prevalent as crucial methodologies and technologies for conducting Data Science. Because these are in the middle of acute developments, sharing the most advanced technologies may be faced by a variety of problems such as digital divide between regions and IP (Intellectual property).
In the present session, the above-mentioned difficulties and challenges in regional collaborations for Data Science will be clearly identified through the case studies that are presented here. The difficulties and challenges identified will be very useful for finding out practical solution to make tangible achievements by regional collaborations.
Transitioning Open data from Being a NOUN to a VERB
Research assessment is the process or a metric which aims to assess the impact of the research study. The assessment may include the process that aims in evaluating the quality or intellect of a researcher given the notion that qualified scientists are more productive and may drive quality research in the process of Scholarly Communications. Over time, we have become used to equating the quality of the research with the quality or performance of the researcher. The emphasis over publications may encourage unethical practices, Which may be extrapolated to the evolution of problems like, Irreproducibility, Scientific fraud.

Over the past century, a myriad of activities has been undertaken or are still being taken to improve the ways by which research can be assessed. Beginning with the first evolution of the Impact Factor and more recently other, Citation metrics, Altmetrics, etc. have resulted from this work. In this article, we discuss around the myriad of strategies that may play a significant role in the cultural transition of Science and Scientists that is still ongoing. And also highlight the reasons why we should not only look at research assessment but should also be keen on researcher evaluations and differentiate them from one another. Reflecting this, the title of the article and the talk signals how the strategies that researchers may need to consider might impact the way they interact with the Open Data movement.

The session highlights the importance of these missing aspects and exemplifies the usage of these strategies to prime open-data momentum and discusses the following paper in an interactive session with live feedbacks from the audience. We intend to use the following advanced tool during the session to live engage the people and derive an interactive session. https://www.sli.do/

The session also includes demo presentation of the tool our organisation has built which embraces all of these missing strategies in it, so to differentiate research vs researchers assessment and also enables publishers and academic society to implement FAIR guidelines at ease in their business as usual workflow. more info about the tool is available at https://www.profeza.com
Big Data in Mining and Metallurgical Technologies: Applications and Prospects
Big data is an entire ecosystem, includingboth platform solutions and various methods and tools designed for collecting,structuring and analyzing large arrays of unstructured data that are invariantto different subject areas.
The sectoral spectrum of applications of big data in mining andmetallurgical technologies is very extensive and covers both the flows ofbillions of discrete particles with individual properties requiring descriptionand testing and the need to create digital databases and models for processingoptimization for natural and technogenic mineral raw materials, as well as forartificial materials. The first class of related tasks includes problems ofcorrect process flow testing at mining enterprises and concentrating factoriesthat extract and process ores of ferrous, non-ferrous, rare and noble metals,as well as coal, in conditions of excessive or insufficient data in terms ofthe material balance in combination with inevitable mistakes and measurementerrors. The second class of related tasks includes the problems of digitalmodeling and optimization of grain-size classification and separation byphysical and physicochemical properties of raw and other materials inindustrial conditions, as well as the creation of digital databases onindustrial methods and process layouts for the separation of natural andtechnogenic raw materials and other materials designed to minimize the scope ofrespective labor-intensive laboratory research.
This session will encompass a discussion of thecurrent tasks and prospects for collecting, storing, processing and analyzingbig data sets and the making of important management and production-relateddecisions in the mining and metallurgical industries based on respectivestudies. Discussions are also scheduled covering the applicable platformsolutions offered by the leading IT companies for implementing sectoral tasks,as well as the existing methods and tools for analyzing big data taking intoaccount characteristic features of these industries. Examples of specificindustry solutions will be considered as implemented by well-known Russian andforeign research centers and companies in the processing of various materials,as well as in the creation of new materials with predetermined properties.
Geospatial data and applications in Earth’s sciences
Geospatial information and technologies play a significant role in a wide range of applications and research sectors, supporting planning and decision making in the academic, governmental, commercial, and non‐profit domains. To foster the growing demand of geospatial data, tools, technologies, and expertise scientific and governmental institutions across the globe are developing reliable geospatial information infrastructures and implementing appropriate policies. This session will focus on the topical issues in the area of geospatial data and technologies in Earth’s sciences. Among others the problems of organization and management of the vast arrays of geospatial information, which is acquired at many levels and that has a variety of potential uses, will be discussed. Another topic for discussion is data sharing in the academic, governmental, commercial, and non-profit domains on national and international levels.

The discussion will also focus on the implementation of modern geospatial technologies in the area of Earth’s sciences, where they play an essential role. This scientific domain is experiencing a significant increase of observational data volumes. It is provided by the development and extension of geophysical monitoring networks that implement modern geophysical instrumentation that provides accurate data with a constantly increasing sampling rate. Within the past decades several specialized geophysical and remote sensing satellite missions have been successfully launched: CHAMP, GOCE, Swarm, and many others. These missions also provide highly-accurate geophysical data with global coverage to the international scientific community. The continuous growth of geospatial data on Earth’s sciences requires adequate methods for their efficient processing and analysis. This becomes one of the most important and widely discussed issues among data science experts and multi-disciplinary communities. Recent advances in geoinformatics, systems analysis approach and data mining techniques address this challenge to a certain extent. In particular, these methods are universal enough to be applied to any geospatial data on Earth’s sciences of any volume in the pattern recognition problem.
Coordination of Data Standards and Interoperability in Agricultural Research: Gaps, Overlaps, Challenges and Future Directions
Current efforts to define, implement and coordinate agricultural research data standards are driven by issues related to interoperability, cost and quality. In addition, the aspirations to obtain value from existing agricultural datasets, agricultural productivity concerns, and desires to speed agricultural research findings to the user community are critical factors that call for effective coordination. The recent opportunities in agricultural research data to drive change in the next decade, coupled with the current emphasis on adoption of Big Data solutions and Data Cubes concept in agriculture sector, underscore the urgent need for coordination of data standards and interoperability in agricultural research.

Agricultural sciences include methods from different disciplines used to generate data to solve problems related to food, nutrition and rural life. As part of these methodologies, data integration is an integral part of this enterprise. New opportunities, like digitisation and machine actionable knowledge organisation, offer new ways to work that were not conceivable for past generations of researchers. Shared vocabularies and other standards for knowledge representation are critical in reducing the effort required to integrate data, and agriculture community must join with closely related communities in environmental sciences in developing these and establishing best practices in maintaining them. Communities working on specific issues can benefit from it, but first research communities need to develop new ways of working and cooperating.

There are various initiatives amongst agricultural researchers and knowledge workers to form the social foundations for these new ways of collaboration. Such initiatives have as a result community recommendations on how to use existing standards for a particular topic. Another approach is topical. See for example the Wheat Data Interoperability Guidelines. These recommendations were prepared by members of the Wheat Data Interoperability Working Group (WG), one of the WGs of the Interest Group on Agricultural Data (IGAD) at the Research Data Alliance (RDA). The group is coordinated by members of the Wheat Initiative, a global initiative that aims to reinforce synergies between bread and durum wheat national and international research programmes to increase food security, nutritional value and safety while taking into account societal demands for sustainable and resilient agricultural production systems. Within the framework of IGAD/RDA there are more working groups based on themes. Currently IGAD hosts wheat data, rice data, other crops, soil data, on-farm data sharing, AgriSemantics, and indicators for scientific and societal impact in agriculture.

At a more general level, the GODAN Action project has brought forward the idea of building a global map of data standards for food and agriculture: spanning across and beyond specialized communities and beyond research, the map tries to give a comprehensive inventory of data standards of all types that can help make all types of agriculture-related data more interoperable and reusable. It is also designed to allow for the assessment of data standards in terms of content, authoritativeness, usability and openness and it can therefore support gap analysis exercises.

Additionally, some of other initiatives related organize themselves regionally, like the CODATA agricultural working group that concentrates on Eastern Africa, and looks into improved findability and accessibility of agricultural data. This panel will concentrate on critical success factors for regional and topical initiatives, and how to reach out to the wider community. CODATA is establishing a Commision on Standards to coordinate practices across the various science communities and also to address the problem of who manages standards that sit above all the disciplines, such as units-of-measure. RDA host a number of working groups and interest groups concerned with vocabulary and terminology standardization.

The e-ROSA project is also relevant. It seeks to build a shared vision of a future sustainable e-infrastructure for open science in agriculture thanks to the co-development of a common roadmap by and for involved research communities and key stakeholders related to scientific data and research infrastructures. The e-infrastructure is seen as an ecosystem of federated services to support data storage, interoperability, integration, discovery, processing, analysis and valorisation.

GEOGLAM is the Group on Earth Observations Global Agricultural Monitoring Initiative. The main objective of GEOGLAM is to reinforce the international community's capacity to produce and disseminate relevant, timely and accurate forecasts of agricultural production at national, regional, and global scales by using Earth Observation data.

This panel session will review the motivations and requirements for standardization of agricultural research data, and the current state of standards development, interoperability issues and adoption–including gaps and overlaps–in the agriculture sector. Relevant areas not yet addressed and informatics challenges related to interoperability, adoption of agricultural research data and terminology standards are key.

Key-note speakers

Meet the professionals
Barbara Ryan
Pavel Kabat
Fred Roberts
Catriona MacCallum
Vladimir Mau

Key dates

Before the opening...
Registration open
Abstract submission deadline
Session submission deadline
Abstract acceptance
Registration closed
Tentative Program
Day 1
Show daily schedule
Day 2
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Day 3
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Day 4
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Day 5
Show daily schedule
registration of the participants
Ice-breaking reception
registration of the participants
Opening Ceremony
Key-session: Fred Roberts
Keysession: Pavel Kabat
coffee break
Session 15: Geological data-driven science of the Arctic
Session 16: Data mining aimed at seismic hazard and risk assessment and ...
Session 37: Data Policy, FAIR Data, Legal Issues and the Limits of ...
Session 10: Modern strategies for data collection and analysis for ...
Session 28: Smart Cities
Session 16 (continue)
Session 43 : Regional Collaboration for Data Science
coffee break
Session 10 (continue)
Session 12: Historical Disaster Data Management and Data Publishing
Session 32: Institutional RDM services
Session 16 (continue)
Key-session: Barbara Ryan
Key-session: Vladimir Mau
coffee break
Session 11: Earth observing systems and data for global energy ...
Session 39: Data and Disaster Risk Research
Session 34: A World Tour of Progress toward Open Data and ...
Session 19: Great earthquakes and tsunamis in subduction zones
Session 39 (continue)
Session 34 (continue)
Session 22: Big Data in Scientific and Commercial Sectors
Session 19 (Continue)
coffee break
Panel Discussion
Key-session: Catriona MacCallum
coffee break
Session 40: Data Platforms for Earth Observation and Interoperability
Session 9: Data Driven Knowledge-Based Systems for Basic and Applied ...
Session 36: Practice and Impact of Data Citation
Session 22 (continue)
Session 40 (continue)
Session 22 (continue)
Session 17: Research data - a multi-dimensional peg in academic ...
Session 35: Coordination of Data Standards and Interoperability in Agricultural ...
coffee break
Session 40 (continue)
Session 41: Open Data and Education
Session 22 (Continue)
Session 17 (Continue)
Closing Dinner
Session TBA
Session 44: CODATA Constants and Mathematical Data Analysis
Session 23: Transitioning Open data from Being a NOUN to a VERB
Session 30: Developing & adopting digital standards for fair ...
coffee break
Session 13: Big Data in Mining and Metallurgical Technologies: ...
Session 26: Geospatial data and applications in Earth’s sciences
Session 38: Data Analysis and Big Data - Health
Session 13 (continue)
Session 26 (continue)
Session 38 (continue)
coffee break
Session 13 (Continue)

Conference committees

Program committee
Vladimir Vasilyev
An active corresponding member of the Russian Academy of Sciences and the Russian Academy of Education. The head of the Council of St. Petersburg Rectors since 2004 and is a member of the St. Petersburg Governor's Technical Council. Rector of Saint Petersburg National ITMO University. The prominent scientist in the fields of computer telecommunications and mathematical modeling of information systems and multifunctional equipment complexes.
Geoffrey Boulton
Regius Professor Emeritus of Geology at the University of Edinburgh and a former Vice Principal of the University. The chair of the Academic Advisory Council of the University of Heidelberg, a member of the Strategic Council of the University of Geneva, President of CODATA, the ICSU body responsible for the constants of science, and president of the Scottish Association for Marine Science. His research is in the fields of environmental geology and glaciology, and he is currently leading a major project on the Antarctic Ice Sheet.
Leonid Vaisberg
Founder and permanent scientific supervisor of REC "Mekhanobr-technika". Academician of RAS, Doctor of Technical Sciences, Professor, well-known expert in the field of processing of all types of materials, a leader in theoretical substantiation and creation of innovative resource-saving technologies for the disintegration and separation of natural, man-made and artificial materials in the processes of their deep processing based on effects of vibrational mechanics and mineralogical features of materials. Professor of St. Petersburg Mining University and Peter the Great St. Petersburg Polytechnic University.
Cyndy Chandler
Information Systems Specialist. Information systems technology specialist with oceanographic research. Marine Chemistry & Geochemistry Marine Chemistry and Geochemistry chandler (MC&G), co-manager of Biological and Chemical Oceanography Data Management Office (BCO DMO), providing comprehensive data management support for select U.S. NSF OCE, PLR ANT and ARC funded projects; data processing and quality control; collaboration with data curators from US and International ocean research projects; integration of Semantic Web technologies.
Alevtina Chernikova
Rector of National University of Science and Technology MISIS. Author of more than 120 publications, including more than 90 scientific papers and 30 teaching aids. Has a reward from Government of the Russian Federation in the field of education. Was awarded the medal "Merits for the Belgorod land" of the II degree, the "Golden memorial sign of MISiS" and the medal "For impeccable service of MISiS" of the I degree, was awarded the title "Honored worker of higher professional education of the Russian Federation", has the gratitude of the Federal Agency for Education.
Michael T. Clegg
Professor emeritus, Ecology & Evolutionary Biology School of Biological Sciences. Past Foreign Secretary, US National Academy of Sciences. Ph.D., University of California, Davis, 1972
Alexei Gvishiani
Academician of the Russian Academy of Sciences, Doctor of Science in Physics and Mathematics, Professor, Director of the Geophysical Center RAS, Chairman of the National Geophysical Committee RAS, Deputy Academician-Secretary of the Earth Science Branch of RAS, member of the Council of Federal Agency of Scientific organization of Russia. Professor of Lomonosov MSU and the Institute of Physics of the Earth, Paris. The vice-chair and a member for Russia of the Scientific Council of the IIASA, Austria. RAS delegate to the ICSU and CODATA.
Heide Hackmann
Executive Director International Social Science Council (ISSC). Heide Hackmann has worked as a science policy maker, researcher and consultant in the Netherlands, Germany, the United Kingdom and South Africa. She holds a PhD in science and technology studies from the University of Twente in the Netherlands.In her research work at the Universities of Stellenbosch (South Africa), Bielefeld (Germany), Keele (UK) and Twente (Netherlands), she has specialized in science policy studies, the governance of science, and research evaluation.
Simon Hodson
Co-chair of the RDA-WDS Data Publication Working Group on Cost Recovery for Data Centres; co-chair of the CODATA-RDA Data Working Group for Data Science Summer Schools in Developing Countries. Expert on data policy issues and research data management. Recently contributed to reports on 'Current Best Practice for Research Data Management Policies, A Report for the Danish e-Infrastructure Cooperation and the Danish Digital Library' and on strategic research data management infrastructure development for a consortium of UK research institutions.
Alik Ismail-Zadeh
Senior Research Fellow, Geophysikalisches Institut, Universität Karlsruhe, - Professor (part time), Institut de Physique du Globe de Paris, - Chief Scientist, Head of Section “Computational Geodynamics” , and Research Professor , International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences - Co-Leader of Research Group “Numerical Methods in Geophysics”, Institute of Mathematics and Mechanics, Russian Academy of Sciences - Visiting Lecturer and Senior Scientist, Abdus Salam International Centre for Theoretical Physics.
Pavel Kabat
Director General and Chief Executive Officer of the International Institute for Applied Systems Analysis. Full Professor of Earth System Science at Wageningen University in the Netherlands, Founding Chair and Director of the Royal Dutch Academy of Sciences and Arts Institute for Integrated Research on the Wadden Sea Region, a Member of the Leadership Council for the United Nations Sustainable Development Solutions Network, and Co-Founder of the High Level Alpbach – Laxenburg Group.
Gennadiy Leonov
Vice-rector of Saint-Petersburg State University from 1986 to 1988. A dean of the Mathematics and Mechanics Faculty. Was awarded Prize of St.-Petersburg State University, State Prize of USSR , Prize of Technische Universitet Dresden. Member of the Russian National Committee of Theoretical Mechanics, member of Directorate of St.-Petersburg Mathematical Society, director of Research Institute of Mathematics and Mechanics of St.-Petersburg State University. Fields of interest: theory of stability, nonlinear oscillations, chaos.
Virginia Murray
A medical Public Health Doctor. Was appointed as Consultant in Global Disaster Risk Reduction for UK’s Public Health England in April 2014. A member of the ICSU Scientific Committee for the Integrated Research on Disaster Risk and co-chair of the IRDR’s Disaster Loss Data (DATA) project. A member of the UN Sustainable Development Solutions Network for Data.
Nebojsa Nakicenovic
Deputy Director General/Deputy Chief Executive Officer of IIASA, former Professor of Energy Economics at the Vienna University of Technology. Member of the United Nations Secretary General Special Advisory 10-Member Group to support the Technology Facilitation Mechanism; United Nations Secretary General High-Level Technical Group; Member of the Advisory Council of the German Government on Global Change (WBGU); Member of the ICSU Committee on Scientific Planning and Review, and Co-Chair of the Global Carbon Project; Member of the Board, Climate Change Centre Austria.
Alena Rybkina
Chief of the Innovation Technologies Sector of the Geophysical Center of the Russian Academy of Sciences. A specialist data technological studies and development of spherical projection systems aimed at efficient analysis, demonstration and popularization in data research and management. Member of the CODATA Executive Committee with the focus on the organization and structuring the CODATA research projects and bring her experience in the geoscience data management as well as involving young scientists as she did for the Task Group.
Alexander Solovyev
Corresponding member, Russian Academy of Sciences (since 2000). Member of the editorial boards of the journals "Izvestiya. Physics of the Solid Earth" and "Journal of Volcanology and Seismology". Vice-Chairman, the Committee for System Analysis, Russian Ac. Sci. Member, Bureau of the National Geophysical Committee, Russian Ac. Sci. Member, the Russian Expert Council on Earthquake Prediction, Seismic Hazard Assessment and Risk (REC).
Lucilla Spini
Head of Science Programmes, International Council for Science (ICSU) – is a biological anthropologist by training with expertise in global environmental change, sustainable development, international science coordination, science-policy bridging, and S&T capacity-building. Prior managing the Science Programmes at ICSU, she has worked for several UN organizations, including UNESCO, UNU, and the FAO. She is an Alumna of the Sustainability Science Programme at Harvard’s Kennedy School of Government and Old Member of Linacre College (University of Oxford).
Andrei Terekhov
Professor, doctor of physical and mathematical sciences Head of the Systems programming department St. Petersburg University. Russian IT developer who created the Algol 68 LGU Telecommunication systems. CEO and founder of the company Lanit-Tercom Chairman of the Board of the All-Russian Association RUSSOFT. Member of ACM and IEEE CS
Sally Wyatt
Professor of ‘digital cultures in development’, Maastricht University, senior researcher with the Huygens Institute for the History of the Netherlands. Research area: digital media in the production of knowledge in the humanities and the social sciences, the ways in which people incorporate the internet into their practices for finding health information. Was a member of the Working Group that prepared the Science International Accord, ‘Open Data in a Big Data World’. Academic Director of the Netherlands Graduate Research School for Science, Technology and Modern Culture.
Rafael Yusupov
Correspondent member of RAS, Dr. Eng., Professor, Honored worker of Science and Technology of the Russian Federation. Director of the St. Petersburg Institute for Informatics and Automation of RAS. Founder and head of the scientific School on the Theory of Sensitivity of Information-Control Systems and School on the Scientific and Methodological Foundations of Informatization of the Society and its Information Security.
Vladimir Zaborovckiy
Doctor of Engineering Science, professor, Director of the Institute of Computer Science and Technology of the Peter the Great Saint-Petersburg Polytechnic University
Organizing committee
Olga Samokhina
Research scientist of the Innovation Technologies Sector of the Geophysical Center of RAS. A specialist in implementation of modern information and visualization technologies in scientific research and industrial domain.
Tatiana Rybkina
Nina Kornienko
Deputy Director of Research Coordination and Development - Scientific Secretary
Sanja Drinkovic
Administrative Officer for IIASA Council and External Relations, Directorate
Roman Krasnoperov
Ph.D. in Physics and Mathematics, senior research fellow at the Laboratory of Geoinformatics and Geomagnetic Studies. Secretary of the National Geophysical Committee of RAS
Elena Firsova
The Bulletin of the Department of Earth Sciences of RAS correspondent, research scientist
Daria Musaelyan
MGIMO graduate, interpreter, cultural guide, chair's assistant



Venue and Accommodation

St. Petersburg Museum of Art
Address of the venue: Smolenka river, bld. 2, Saint Petersburg, Russia
(59.949747, 30.275305 on Google maps)
The conference sessions has been organised at the St. Petersburg Museum of Art.
The Museum which has lassic and grand halls interior sis located in the historic center of the Vasilyevsky Island, in the 1930s period building with a spectacular Neva river view.
Collection of the St. Petersburg Museum of Art presents permanent thematic expositions works of different arts (graphic, painting, sculptures, scenic and ornamental art) in a holistic composition of the halls' decor.
Location on the map
How to get from...
Sights nearby
From Congress hall to...
7 minutesSportivnaya metro station
City center
37 minutesby walk
18 minutesby taxi
40 minutes Pulkovo Airport
How to get from...
taxi: At Pulkovo Airport we endorse Taxi Pulkovo distinct fully licensed service. If you use Taxi Pulkovo, the airport can guarantee fixed process, safety and high quality of the service. Taxi Pulkovo counters are located at the Baggage-claim area and in the Arrivals hall on the first floor of the Terminal.
minibus: Minivan Taxi number K39 runs between the airport and “Moskovskaya” metro station daily, from 07:00 am till 11:30 p.m. every 5 minutes. Ride time is about 15-20 minutes. The bus stop is in front of Arrivals hall exit. Ticket costs 40 rubles. By metro From Moskovskaya station you can get to Sportivnaya or Vasileostrovskaya station. Way time from these stations to Museum of Art to takes 7 minutes by walk. Ticket costs 45 rubles.
bus subway: City bus number 39 runs between the airport and “Moskovskaya” metro station daily from 05:25 a.m. till 0:55 a.m. Ride time is about 30-35 minutes. The bus stop is in front of the Arrivals hall exit. Ticket costs 40 rubles. All the information important for passengers in announced in English. By metro From Moskovskaya station you can get to Sportivnaya or Vasileostrovskaya station. Way time from these stations to Museum of Art to takes 7 minutes by walk. Ticket costs 45 rubles.
express subway: City express number 39E (express) runs between the airport and “Moskovskaya” metro station daily from 05:25 a.m. till 00:20 a.m. Ride time is about 20 minutes. The bus stop is in front of the Arrivals hall exit. Ticket costs 40 rubles. All the information important for passengers in announced in English. By metro From Moskovskaya station you can get to Sportivnaya or Vasileostrovskaya station. Way time from these stations to Museum of Art to takes 7 minutes by walk. Ticket costs 45 rubles.
taxi: At Moskovsky railway station we endorse Taxi distinct fully licensed service or on-line taxi-Service Uber. Ride time by the taxi is about 25 minutes.
subway: If you travel by train you will arrive to the Moskovsky railway station. The nearest metro station is Ploschad Vosstaniya - at the first red line, and Mayakovskaya - at the third green line. You can get there through the central hall of the building and underpass. By metro From Ploschad Vosstaniya and Mayakovskaya station you can get to Sportivnaya or Vasileostrovskaya station. Ticket costs 45 rubles. Way time from these stations to Museum of Art to takes 7 minutes by walk.
bus: City bus number 10 runs between the Moskovsky railway station and the Museum of Art. Bus stop is on Suvorovskiy avenue 132. Bus goes every 12 minutes. Ticket costs 40 rubles. Ride time is about 45 minutes.
COURTYARD Vasilievsky 4* Website
Sights nearby
Palace Square
Saint Isaaks Cathedral
The Bronze Horseman
Nevskiy Prospect
St Peter and Paul Fortress
Admiralty building
Kazan Cathedral
Michael Palace and Russian museum

Venue and Accommodation

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