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Applications Invited to Participate in the CODATA-RDA Research Data Science Advanced Workshops, Trieste, Italy 2019 - Deadline 18 April 2019
The CODATA-RDA Research Data Science Summer School and Research Data Science
Advanced Workshops will run for their fourth and third year respectively at the International Centre for Theoretical Physics, Trieste, Italy.
The CODATA-RDA Research Data Science Advanced Workshops will take place on 19-23 August 2019. Apply here!
Deadline: 18/04/2019
During this activity, several applied/thematic workshops on Research Data Science run in parallel.
- Bioinformatics: This workshop focuses on building Machine Learning workflows using NGS Data. Topics include: Experimental design; Introduction to NGS data analysis; Machine Learning in NGS; and CWL. Participants should be familiar with UNIX shell and R programming language.
- IoT and Big Data Analytics: This workshop presents the analysis of vast amounts of data produced by embedded devices, sensors, appliances and other data-collecting systems in real time using new processes and tools for collecting, storing and processing IoT big data, event/streaming data. Participants should be familiar with software installation and programming in R or Java or Python. Professionals & corporate entities should apply for this workshop via the ITU Academy.
- Climate Data Sciences: This workshop will introduce Cloud-Computing based Data access, processing and visualisation tools for Climate Science, including the Copernicus climate data services platforms and the CMIP Earth System Grid. Participants will work in small project teams and should have a background in Climate Sciences and/or climate modeling.
- Extreme Sources of Data: This workshop introduces the basics relative to a cut-and-count particle physics analysis as performed in the ATLAS Collaboration (Large Hadron Collider). Topics to be covered include phenomenological, experimental and data-analysis aspects of the Standard Model; software development and tools for analysis and reproducible science and sharing. Participants should have taken at least one course on Particle Physics at High Education level.
Individuals seeking an introduction to Research Data Science can apply to the
Summer School that runs immediately before the workshops.
Grants:
- A limited number of grants are available to support the attendance of selected participants from developing countries.Professionals and corporate entities should register/apply for the Advanced Workshop on IoT and Big-Data Analytics via the ITU Academy platform.
Sponsors
About the CODATA-RDA Research Data Science Summer School, 5-16 August 2019
The CODATA-RDA Research Data Science Summer School provides training in the foundational skills of Research Data Science. Contemporary research – particularly when addressing the most significant, transdisciplinary research challenges – cannot be done effectively without a range of skills relating to data. This includes the principles and practice of Open Science and research data management and curation, the use of a range of data platforms and infrastructures, large scale analysis, statistics, visualisation and modelling techniques, software development and annotation and more. We define ‘Research Data Science’ as the ensemble of these skills.
Find out more about the schools
here where you will find links to information about past schools in 2016, 2017 and 2018 held in Trieste and São Paulo. Watch a video about the Schools of Research Data Science
here
The School of Research Data Science has enjoyed a remarkable success and clearly responds to a burning need for data skills among Early Career Researchers and others involved in the research process, internationally.
ICTP School Poster for DataTrieste 2019
Applications Invited to Participate in the CODATA-RDA Research Data Science Summer School, Trieste, Italy 2019 - Deadline 18 April 2019
The CODATA-RDA Research Data Science Summer School and Research Data Science
Advanced Workshops will run for their fourth and third year respectively at the International Centre for Theoretical Physics, Trieste, Italy.
The CODATA-RDA Research Data Science Summer School will take place on 5-16 August 2019. Apply here!
Deadline: 18/04/2019
This school provides Early Career Researchers (at MSc-level to 3 years after their PhD) and Professionals (who register via ITU Academy) with the necessary set of foundational Data Science skills to enable them to analyse their data in an efficient and effective manner for the 21st century.
The material covered here is fundamental to all areas of Data Science and hence open to researchers from all disciplines that deal with significant amounts of data. The focus is to provide a practical introduction to these topics with extensive labs and seminars.
Topics:
- Open Science
- Introduction to Unix Shell
- Programming for Analysis
- Git
- Research Data Management
- Author Carpentry
- Data Visualisation
- Information Security
- Machine Learning
- Computational Infrastructures
Individuals with a background in High Energy/Particle Physics, IoT/Big-Data Analytics, Bioinformatics and Climate Data Sciences can apply to one of the
Advanced workshops that run immediately after the school.
Grants:
- A limited number of grants are available to support the attendance of selected participants from developing countries.
- Professionals and corporate entities must register and apply via the ITU Academy platform.
Sponsors
About the CODATA-RDA Research Data Science Summer School, 5-16 August 2019
The CODATA-RDA Research Data Science Summer School provides training in the foundational skills of Research Data Science. Contemporary research – particularly when addressing the most significant, transdisciplinary research challenges – cannot be done effectively without a range of skills relating to data. This includes the principles and practice of Open Science and research data management and curation, the use of a range of data platforms and infrastructures, large scale analysis, statistics, visualisation and modelling techniques, software development and annotation and more. We define ‘Research Data Science’ as the ensemble of these skills.
Find out more about the schools
here where you will find links to information about past schools in 2016, 2017 and 2018 held in Trieste and São Paulo. Watch a video about the Schools of Research Data Science
here
The School of Research Data Science has enjoyed a remarkable success and clearly responds to a burning need for data skills among Early Career Researchers and others involved in the research process, internationally.
ICTP School Poster for DataTrieste 2019
DEADLINE EXTENDED TO 4 MARCH - Call for Papers, Drexel-CODATA FAIR and Responsible Research Data Management Workshop, 31 March-1 April
FAIR and Responsible Research Data Management (FAIR-RRDM)
A Drexel Metadata Research Centre and CODATA workshop on knowledge sharing between research communities and research institutions
Sun 31 March and Mon 1 April 2019, Drexel University, Philadelphia, USA, as a colocated, pre-event to the 13th RDA Plenary
Responsible data management embodies the FAIR principles of making data findable, accessible, interoperable, and reusable. FAIR has helped focus minds and provided readily adopted terminology and guidelines, which in turn will help realise the benefits of accelerated analysis, with machines, at scale. In consequence, research communities and research institutions are faced with the task of rising to the challenge of FAIR and responsible data management.
Advancing the adoption of FAIR requires sharing protocols, practices, policies, methodologies, and approaches for responsible data management. The open science and open data movements have made significant progress in certain research communities and domains, but less so in others. While good practices have been developed within some research communities, it is in research institutions and universities that data management and some long term stewardship must take place. Sometimes reluctantly, research institutions have been obliged to take greater responsibility for research data management by the needs of researchers and their communities on the one hand and by the requirements of national funders on the other.
There are opportunities for knowledge sharing and coordination across a number of these axes: between research disciplines and communities; between research communities and institutions; and internationally among institutions. The biomedical and genomics fields, for example, have made considerable progress with data sharing and with issues of nomenclature and semantics. Much research activity of the last two decades could not have happened without community agreements on data sharing and mechanisms for managing concepts, semantic specifications and ontologies. Likewise, many biomedical research domains are addressing the challenges of controlled sharing of sensitive and restricted data, following the FAIR principles but with respect to ethical and legal criteria where these prevent certain data from being fully Open.
The aim of this workshop is to bring together researchers, data management experts, policy leaders and to facilitate knowledge sharing between research communities and between institutions. Perspectives from all domains and from research institutions are in scope. At least one session will examine progress in the biomedical community and lessons to be learnt, particularly in relation to good practice and mechanisms for controlled sharing of sensitive and restricted data.
Call for Presentations and Posters/Lightning Talks
The deadline for proposals is Mon 4 March and accepted speakers will be notified no later than Tue 12 March.
Recommended proposal lengths for the three categories of presentation are:
Long, research presentation, addressing the workshop themes by reporting on an original research activity: 800-1200 words
Short, practice presentation, addressing the workshop themes by reporting on a project or institutional activity: 400-800 words
Poster and lightning talk addressing the workshop themes: 300-600 words
After the workshop, selected presenters will be invited to submit a full paper to the
CODATA Data Science Journal where they will form a special collection.
Workshop Themes / Sessions
- FAIR data: implications and responsibilities 1) for research communities and 2) for research institutions.
- FAIR data stewardship and knowledge sharing. What progress has been made in RDM and FAIR data stewardship? What can be learnt from biomedical research and from other domains?
- Limits of open data and how do deal responsibly with sensitive data. What can be learnt from biomedical fields and other fields for the controlled sharing of sensitive data?
- RDM, FAIR stewardship services and research infrastructures 1) for research communities and 2) for research institutions. How are research communities and/or research institutions implementing research infrastructures for RDM and FAIR stewardship? How are they tackling related and supporting issues such as: a) developing skills and capacity; b) addressing policy, legal and ethical issues; c) aligning strategies and priorities with FAIR and RDM responsibilities?
- Alignment of domain and institutional RDM and FAIR stewardship: What experiences exist and mechanisms are there for aligning domain and institutional RDM and FAIR stewardship? Examples of collaboration between research communities, domain research infrastructures and institutions will be particularly welcome.
Registration
Sponsorship
The programme committee and organisers are committed to ensuring this is a no-fee event. To help with this ambition, we will be very grateful for financial support and sponsorship. Please contact Jane Greenberg <
jg3243@drexel.edu>, Simon Hodson <
simon@codata.org> for further information.
Call for Sessions: CODATA 2019 - Towards next-generation data-driven science: policies, practices and platforms
The CODATA 2019 Conference will be held on 19-20 September 2019 in Beijing, China. This year’s conference theme is: Towards next-generation data-driven science: policies, practices and platforms. The conference will follow a high-level workshop, 17-18 September 2019, on ‘Implementing Open Research Data Policy and Practice’ that will examine such challenges in China and elsewhere in the light of the emergence of data policies and in particular the China State Council’s Notice on ‘Measures for Managing Scientific Data’.
CODATA 2019: Towards next-generation data-driven science: policies, practices and platforms
Science globally is being transformed by new digital technologies. At the same time addressing the major global challenges of the age requires the analysis of vast quantities of heterogeneous data from multiple sources. In response, many countries, regions and scientific domains have developed Research Infrastructures to assist with the management, stewardship and analysis. These developments have been stimulated by Open Science policies and practices, both those developed by funders and those that have emerged from communities. The FAIR principles and supporting practices seek to accelerate this process and unlock the potential of analysis at scale with machines. This conference provides a significant opportunity to survey and examine these developments from a global perspective.
The convening organisations are pleased to invite you to contribute to the program by proposing sessions. The deadline for session proposals is 15 April 2019: https://conference.codata.org/CODATA_2019/submit/
All proposals related to open science and open data, FAIR data, research data management and stewardship, research infrastructures and platforms are welcomed. The following themes are of particular interest:
1. FAIR and Open data policies
- Open data policies, their implications and implementation
- FAIR data, its challenges and opportunities
- Incentives and metrics for data and research contribution
- Trustworthiness and sustainability for FAIR data, research infrastructures, data repositories
- Co-operation in research data policies and management at international, national and institutional levels
- Data policies towards the next-generation open science community
2. Advanced research infrastructures for Open Science and FAIR data
- Opportunities and challenges in research infrastructures.
- Disciplinary technical infrastructure for research data management and data stewardship.
- The development of Open Science Clouds, Platforms and Commons: a new model for coordination?
- Successes and models for different aspects of the research data management and stewardship infrastructure
- Institutional research data management and stewardship status, models and challenges.
- Data management technologies and interoperability between human and technical processes.
- Data science education and training.
- Business models for Open Science, FAIR data, research infrastructures and data stewardship.
- Key data specifications, RDM protocols and research infrastructures
- Other technologies and standards feature open data issues.
3. Data driven scientific discovery and decision-making.
- Case studies and exploration of science discoveries based on data-driven research
- Data-driven decision-making, from data to evidence
- Disciplinary data applications
- Data success stories
4. Data intensive research for international scientific and global challenges
- FAIR data, interoperability and data integration in multi-disciplinary research areas.
- Data-driven practices in support of the United Nation’s sustainable development goals.
- Data-driven practices in support of Sendai and disaster risk reduction
- Data-driven practices in support of Resilient Cities; biodiversity; climate change adaptation; agriculture; hydrology and other research areas.
Programme
- Sessions: Sessions will be 90 minutes. Two session formats are suggested: 1) papers sessions which may include research papers, practice papers or a mixture of these; 2) lightning talks followed by a structured panel discussion. Paper presentations should be a minimum of 15 minutes; papers sessions should include a maximum of 4-5 papers.
- Keynote speakers: there will be keynote sessions on the morning of each day.
- Plenary panel discussion: the conference will close with a Plenary Panel discussion featuring short presentations.
- Poster session: there will be a poster session on the later afternoon of the first day.
Important dates:
1 February: Call for Session Proposals Released
1 April: Registration Open
15 April: deadline for session proposals
30 April: accepted session proposals notified; call for presentations and posters released.
31 May: deadline for presentation submissions and first round of poster submissions
30 June: submitters notified of acceptances of full presentations and posters
1 August: close of second round of poster submissions
18 August: close of early bird registration
19-20 September: CODATA 2019 Conference ‘Towards next-generation data-driven science: policies, practices and platforms’
Organization
- Convenors: CODATA, CODATA China
- Supporter: Minister of Science and Technology (MOST), Chinese Academy of Sciences (CAS), NSFC
- Local organiser: Computer Network Information Center, CAS; National S&T Infrastructure Center, MOST
Possible venue (TBC): the Friendship Hotel of Beijing.
The Friendship Hotel of Beijing is one of the largest garden-style hotels in Asia. Located in the heart of ZhongGuanCun Hi-Tech Zone, the Friendship Hotel neighbours many world famous tourist sites and universities such as Tsinghua and Peking University, the Summer Palace.
Address: Zhongguancun South St. Beijing 100873, P.R. China
Website: http://www.friendshipshotel.com/en/
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This document provides a quick and accessible list of activities, deliverables and impact from the past year. It then highlights some important upcoming activities and events for 2019.