This document discusses how the BlueBRIDGE project supports open science skills building through virtual research environments. It outlines the challenges of integrating scattered data and tools for educational courses. BlueBRIDGE addresses these challenges by automatically creating tailored environments for each course that integrate various data processing services and models. This enables collaborative research and experimentation while managing access policies and reproducibility. BlueBRIDGE closes the gap between scientific and educational environments and promotes open science practices.

1. BlueBRIDGE receives funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No. 675680 www.bluebridge-vres.euBlueBRIDGE receives funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No. 675680 www.bluebridge-vres.eu
Supporting Open Science Oriented
skills building
by Virtual Research Environments
Digital Infrastructures for Research
November 30 2017
Brussels, Belgium
Pasquale Pagano
BlueBRIDGE Technical Director
CNR-ISTI
pasquale.pagano@isti.cnr.it

2. Outline
Supporting Open Science Oriented skills building by Virtual Research Environments
BlueBRIDGE
Requirements
for
Open Science
Delivering
Capacities for OS
Skills Building
2

3. BlueBRIDGE objective
To exploit the new technological landscape for facilitating
communities of scientists, innovators from SMEs and educators
from different domains in their knowledge production chain,
from the initial phases, data collection and aggregation, to the
production of indicators for competent authorities and investors.
Supporting Open Science Oriented skills building by Virtual Research Environments 3

4. BlueBRIDGE Services Offer
Tailored services addressing three heterogeneous domains
One common infrastructure
D4Science
Infrastructure
Supporting Open Science Oriented skills building by Virtual Research Environments 4

5. BlueBRIDGE Infrastructure Services Offer
Supporting Open Science Oriented skills building by Virtual Research Environments
Data services addressing the whole data management value chain
Infrastructure services addressing the access and management of
infrastructure resources
5

6. BlueBRIDGE hides ICT complexities
Supporting Open Science Oriented skills building by Virtual Research Environments
Storage
Database GIS NoSQL
Computing
D4Science EGI SeaDataNet
Data
OSCAR Copernicus
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7. BlueBRIDGE hides ICT complexities
Data and
Services
Hosted by different
Organizations
Accessible through
different Protocols
Described with
different Metadata
Policies
Different Licenses
Different Terms of Use
Different approaches
for Credits
Heterogeneity
Provide Discovery,
Access, Use
Support Validation,
Curation,
Harmonization
Trace Provenance
Supporting Open Science Oriented skills building by Virtual Research Environments
BlueBRIDGE provides solutions for dealing with modern science
increasingly global, multi-disciplinary and networked
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8. REQUIREMENTS FOR
OPEN SCIENCE
Providing researchers with the skills and competencies they need to
practise Open Science
Courtesy of Open Science Skills Working Group
Supporting Open Science Oriented skills building by Virtual Research Environments 8

9. Vision
Supporting Open Science Oriented skills building by Virtual Research Environments
When all researchers are aware of
Open Science, and are trained,
supported and guided at all career
stages to practice Open Science,
the potential is there to
fundamentally change the way
research is performed and
disseminated,
fostering a scientific ecosystem in
which research gains increased
visibility, is shared more efficiently,
and is performed with enhanced
research integrity
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10. Categories of
Open Science Skills
Supporting Open Science Oriented skills building by Virtual Research Environments
Skills and expertise necessary for open access publishing.
Skills and expertise regarding research data, data production,
management, analysis/use/reuse, dissemination and a change of
paradigm from “protected data by default” to “open data by
default”, respecting legal, and other constraints.
Skills and expertise to act in and beyond one’s own scholarly and
disciplinary community.
Skills and expertise resulting from a general and broad concept of
citizen science, where researchers interact with the general public
to enhance the impact of science and research.
10

11. Data Science Competences
Supporting Open Science Oriented skills building by Virtual Research Environments 11

12. Recommendations
Supporting Open Science Oriented skills building by Virtual Research Environments
Recommendation 5: Providing Support for Open Science
Provide the technical infrastructure for Open Science (high-
speed data centres, data repositories and virtual platforms).
Provide the technical tools to facilitate researchers in doing
Open Science (software for data creation, storage, and sharing).
Provide professional support staff for general and specialist
support for researchers (data stewards, IT technicians, data
scientists, legal experts, discipline specific data managers and
librarians).
Implement and promote the use of data management plans in
all research projects.
Ensure a legal framework is in place for the secure, legal, and
ethical sharing of data.
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13. DELIVERING CAPACITIES
FOR OPEN SCIENCE SKILLS BUILDING
Challenges, best practices, and technologies for …
Supporting Open Science Oriented skills building by Virtual Research Environments 13

14. Challenges
Supporting Open Science Oriented skills building by Virtual Research Environments
The scattered nature of facilities and data of
potential interest for a course or for an
instructor,
the ever growing multidisciplinary nature of
courses,
the aim to reduce as much as possible the
distance between the way scientists work, the
latest research results and what the students
are provided with
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15. Practical Challenges
Supporting Open Science Oriented skills building by Virtual Research Environments
All the steps in preparing course supporting environments
require manual work, which is repeated each time a new
course is held.
Available data processing services and models come under
heterogeneous programming languages, which usually require
installing complex software on users’ computers.
Executing models on users’ data usually demands a long phase
of data preparation and powerful hardware, not always
available in the institutions laboratories.
Sharing data, parameters and results of experiments is difficult
and collaboration between teachers and students is limited to
the duration of the physical course.
No instrument exists that currently bridges the scientific
environments with the training environments.
15

16. Delivered Capacities
Supporting Open Science Oriented skills building by Virtual Research Environments
An easy, automatic, and costless way to
create a new tailored environment for each course
Integrate data processing services and models
Store and make accessible data
Support collaborative research and experimentation
Implement Reproducibility-Repeatability-Reusability
Manage heterogeneous data/processes access policies
low operational and low maintenance costs
16

17. Environment Preparation
Trainer
Supporting Open Science Oriented skills building by Virtual Research Environments 17

18. Environment Exploitation
Trainer
Updates the script on
his private Workspace
The service downloads
the script on-the-fly
A trainee executes
an experiment on
his/her data
The output, the input and the
parameters can be shared with
trainees and with the trainer
Either the trainee or the
trainer can execute the
experiment again
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Supporting Open Science Oriented skills building by Virtual Research Environments 18

19. Integrating New Processes
Integration: putting a script/software that works offline into the
Cloud computing platform.
• Software can be written in R, Python, Java, Octave, Linux
compiled, Windows compiled, Knime Workflow.
e.g. R script
Computing platform Web interface and Web service
SAI - Importing tool
Automatic
Supporting Open Science Oriented skills building by Virtual Research Environments 19

20. Advantages
Tools and software are available also as-a-Service
Can be invoked via communication standards
Can exploit higher computational capabilities
Becomes accessible via a Web interface
Data generated through the integrated tools
are empowered with provenance management
store the results on a high-availability storage
The course environment (VRE) enables
Security, accounting and multi-tenancy
Collaboration and sharing
Re-usability, Reproducibility, Repeatability - also using other
software (e.g. QGIS)
Supporting Open Science Oriented skills building by Virtual Research Environments 20

21. Conclusions
• BlueBRIDGE simplifies the integration of tools
and software into e-infrastructure
• BlueBRIDGE ensures access to an integrated
environment designed by the trainer
• BlueBRIDGE closes the gap between scientific
and training environments
• BlueBRIDGE promotes open science practices
by enabling them transparently
Supporting Open Science Oriented skills building by Virtual Research Environments
BB manages
BB supports
BB operates
Users exploits
Policies
Authz
ToU
Training
Adoption
Use
Monitoring
Accounting
Provision
Security
Discover
Access
Re-use
Share 21

22. Thank You
Questions?
Supporting Open Science Oriented skills building by Virtual Research Environments 22
Visit the BlueBRIDGE Website:
http://www.bluebridge-vres.eu
Visit the BlueBRIDGE Catalogue & VREs:
https://bluebridge.d4science.org/catalogue