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2016 Conference on Big Data from Space
BiDS’16
Tenerife, Spain
March 16, 2016
Nadia Nardi, Engineering
The D4Science
Infrastructure to Support
Academic Courses
• A perspective of the educational path
• Do (data) scientists, students have access to explore an
operational data platform and gain hands-on experience
on real scientific challenges?
• Is there a workspace that exists where to create and
consume academic courses in an optimal manner?
• What would an optimal workspace be like?
www.eng.it2
our 20 mins
www.eng.it3
perspective of educational
path
• Education + Research & Innovation = priorities of EU
Investments to boost jobs and growth
• To be able to promote and exploit Data, such as Space
Data, a clever workspace, a training environment, is
needed to support ONE trainees (data scientists) and
TWO trainers
www.eng.it4
problem ?
• Trainees need the possibility to work on an operational
data platform
• Experiments and academic works shouldn’t just be done
on simulated environments or sample data sets
• Trainees need access to a data platform that supports
manipulation and management of data (of any nature)
www.eng.it5
problem ?
• There is lack of technological support - preparing courses and
workshops require manual work, which is repeated each time a
new course is held because of the need to reset and reconfigure
the training environment for the next course
• 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 requires a long phase of
data preparation and powerful hardware (not always available in
the labs)
• Sharing data, parameters and results of experiments is difficult
and collaboration between trainers and trainees is limited to the
duration of the course
www.eng.it6
d4science.org
• The D4Science (hybrid data) e-
Infrastructure has been around
since 2004 to support Science
and educational challenges
• Designed to integrate
resources from other e-
Infrastructures and commercial
vendors, offering unified
access to integrated resources
and services
99.7%
service
availability
place
connecting
+2000
scientists
in
44countries
integrating
+55
heterogeneous
data providers
providing access to
> 1 Billion
quality records in
repositories worldwide
Executing
+13000
models/algorithms a
month
osts
+40VRE’s
www.eng.it7
d4science.org
• Supports the operation of a large set of diverse
Initiatives, Communities of Practice, and Projects by
offering Virtual Research Environments (VREs) and
Services
• Aims to offer trainees remote computational facilities to
execute experiments and provide facilities to visualize
datasets and perform analysis
• Serves: biological, ecological, environmental, mining,
statistical communities worldwide
place
www.eng.it8
d4science.org
+50
0
software componets
www.eng.it9
facilities ?
• to manage distributed resources efficiently (monitoring, accounting,
alerting, failure-recovery, scale-in/out)
• for end-users according to the Science 2.0 paradigm (web portal,
workspace, messaging system, social networking)
• for data management (data and metadata harmonization, metadata
generation, data discovery and access)
• to visualize large datasets (GIS maps, graphs, tables)
• to perform data analysis (Artificial Intelligence algorithms; forecasting and
signal processing methods)
• to perform computations on large datasets (cloud computing and high-
throughput computing)
www.eng.it10
bluebridge-vres.eu
Fishery and Marine Sciences Community
•Simplifies the sharing and re-use of knowledge, facilitating cross-fertilization
and collaboration among their actors - supports activities contributing to the
H2020 Blue Growth Societal challenge with a strong focus on sustainable
growth.
•Trainees- have tools to easily discover and access a rich set of structured and
high quality data, can exploit a large variety of always up-to-date models to first
analyse, compare and share resulting datasets, and then to discuss analytical
processes.
•Trainers- lower effort to prepare the environment for the courses, boosting
training programmes, giving them a new volume and a new thematic and
geographic reach.
www.eng.it11
D4Science serves different
scientific and industrial
contexts
• Expliots the e-Infrastructure to support the practical uptake of scientific
knowledge (in workshops and academic courses), leveraging on the offered
capacity
• Specific VREs for education offer services enabling collaboration and
integrated access to digital research resources, cross-disciplinary and
cross-community tools, data and services
www.eng.it12
bluebridge-vres.eu
Some services...
•Stock Assessment Dashboard: efficient assessment of fishery stocks and the
production of related knowledge and indicators.
•Global Record of Stocks and Fisheries Knowledge base: access to evidence
based information on the status of marine stocks and fisheries.
•Aquaculture Atlas Generation: produce aquaculture products (maps of human
activity and natural zones) contributing to an aquaculture atlas compliant with
NASO standards.
•Protected Area Impact Maps Production: production of maps of vegetation
types and human impacts on them to enable ecosystem degradation analysis.
www.eng.it13
bluebridge-vres.eu
Some services...
•Performance Evaluation in Aquaculture Dashboard: support performance
estimation, benchmarking, decision making and strategic investment analysis
in aquaculture.
•Strategic Investment Analysis Dashboard: support identification of strategic
locations of interest for investment meeting multifactor selection criteria.
www.eng.it14
join us
user
group
community
you can manage the communities and offer them a
set of virtual environments
can create your own virtual environment and add the
applications you need
securely preserve, access (from anywhere), and
confidentially share your data and exploit one or more
of the existing applications
home sweet home
www.eng.it15
• Education + Research & Innovation = priorities of EU
Investments to boost jobs and growth.. Right?
• Education must be giving the right importance and effort
to continuously improve the experience for both trainer
and trainee.
• D4Science supports academic courses by taking a
comprehensive approach to what it means to boost
education and facilitate knowledge bridging between
research and innovation… and scientific and training
requirements
• 12 years later D4Science is still here and through
BlueBRIDGE is looking also for new opportunities to
promote interdisciplinary collaboration
Thanks for your attention
www.eng.it16
nadia.nardi@eng.it
time to talk
www.eng.it17
Data Science technologies impact how research is
conducted - how data is used and shared…..
How can e-Infrastructures reflect the needs of Data
Scientist to study/work at best?
What are the training needs specific to this community?

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The D4Science Infrastructure to Support Academic Courses

  • 1. 2016 Conference on Big Data from Space BiDS’16 Tenerife, Spain March 16, 2016 Nadia Nardi, Engineering The D4Science Infrastructure to Support Academic Courses
  • 2. • A perspective of the educational path • Do (data) scientists, students have access to explore an operational data platform and gain hands-on experience on real scientific challenges? • Is there a workspace that exists where to create and consume academic courses in an optimal manner? • What would an optimal workspace be like? www.eng.it2 our 20 mins
  • 3. www.eng.it3 perspective of educational path • Education + Research & Innovation = priorities of EU Investments to boost jobs and growth • To be able to promote and exploit Data, such as Space Data, a clever workspace, a training environment, is needed to support ONE trainees (data scientists) and TWO trainers
  • 4. www.eng.it4 problem ? • Trainees need the possibility to work on an operational data platform • Experiments and academic works shouldn’t just be done on simulated environments or sample data sets • Trainees need access to a data platform that supports manipulation and management of data (of any nature)
  • 5. www.eng.it5 problem ? • There is lack of technological support - preparing courses and workshops require manual work, which is repeated each time a new course is held because of the need to reset and reconfigure the training environment for the next course • 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 requires a long phase of data preparation and powerful hardware (not always available in the labs) • Sharing data, parameters and results of experiments is difficult and collaboration between trainers and trainees is limited to the duration of the course
  • 6. www.eng.it6 d4science.org • The D4Science (hybrid data) e- Infrastructure has been around since 2004 to support Science and educational challenges • Designed to integrate resources from other e- Infrastructures and commercial vendors, offering unified access to integrated resources and services 99.7% service availability place connecting +2000 scientists in 44countries integrating +55 heterogeneous data providers providing access to > 1 Billion quality records in repositories worldwide Executing +13000 models/algorithms a month osts +40VRE’s
  • 7. www.eng.it7 d4science.org • Supports the operation of a large set of diverse Initiatives, Communities of Practice, and Projects by offering Virtual Research Environments (VREs) and Services • Aims to offer trainees remote computational facilities to execute experiments and provide facilities to visualize datasets and perform analysis • Serves: biological, ecological, environmental, mining, statistical communities worldwide place
  • 9. www.eng.it9 facilities ? • to manage distributed resources efficiently (monitoring, accounting, alerting, failure-recovery, scale-in/out) • for end-users according to the Science 2.0 paradigm (web portal, workspace, messaging system, social networking) • for data management (data and metadata harmonization, metadata generation, data discovery and access) • to visualize large datasets (GIS maps, graphs, tables) • to perform data analysis (Artificial Intelligence algorithms; forecasting and signal processing methods) • to perform computations on large datasets (cloud computing and high- throughput computing)
  • 10. www.eng.it10 bluebridge-vres.eu Fishery and Marine Sciences Community •Simplifies the sharing and re-use of knowledge, facilitating cross-fertilization and collaboration among their actors - supports activities contributing to the H2020 Blue Growth Societal challenge with a strong focus on sustainable growth. •Trainees- have tools to easily discover and access a rich set of structured and high quality data, can exploit a large variety of always up-to-date models to first analyse, compare and share resulting datasets, and then to discuss analytical processes. •Trainers- lower effort to prepare the environment for the courses, boosting training programmes, giving them a new volume and a new thematic and geographic reach.
  • 11. www.eng.it11 D4Science serves different scientific and industrial contexts • Expliots the e-Infrastructure to support the practical uptake of scientific knowledge (in workshops and academic courses), leveraging on the offered capacity • Specific VREs for education offer services enabling collaboration and integrated access to digital research resources, cross-disciplinary and cross-community tools, data and services
  • 12. www.eng.it12 bluebridge-vres.eu Some services... •Stock Assessment Dashboard: efficient assessment of fishery stocks and the production of related knowledge and indicators. •Global Record of Stocks and Fisheries Knowledge base: access to evidence based information on the status of marine stocks and fisheries. •Aquaculture Atlas Generation: produce aquaculture products (maps of human activity and natural zones) contributing to an aquaculture atlas compliant with NASO standards. •Protected Area Impact Maps Production: production of maps of vegetation types and human impacts on them to enable ecosystem degradation analysis.
  • 13. www.eng.it13 bluebridge-vres.eu Some services... •Performance Evaluation in Aquaculture Dashboard: support performance estimation, benchmarking, decision making and strategic investment analysis in aquaculture. •Strategic Investment Analysis Dashboard: support identification of strategic locations of interest for investment meeting multifactor selection criteria.
  • 14. www.eng.it14 join us user group community you can manage the communities and offer them a set of virtual environments can create your own virtual environment and add the applications you need securely preserve, access (from anywhere), and confidentially share your data and exploit one or more of the existing applications
  • 15. home sweet home www.eng.it15 • Education + Research & Innovation = priorities of EU Investments to boost jobs and growth.. Right? • Education must be giving the right importance and effort to continuously improve the experience for both trainer and trainee. • D4Science supports academic courses by taking a comprehensive approach to what it means to boost education and facilitate knowledge bridging between research and innovation… and scientific and training requirements • 12 years later D4Science is still here and through BlueBRIDGE is looking also for new opportunities to promote interdisciplinary collaboration
  • 16. Thanks for your attention www.eng.it16 nadia.nardi@eng.it
  • 17. time to talk www.eng.it17 Data Science technologies impact how research is conducted - how data is used and shared….. How can e-Infrastructures reflect the needs of Data Scientist to study/work at best? What are the training needs specific to this community?

Editor's Notes

  1. Add notes from article on heterogeneous of data ....
  2. Add notes from article on heterogeneous of data ....
  3. Add notes from article on heterogeneous of data ....
  4. Add notes from article on heterogeneous of data ....
  5. The D4Science e-Infrastructure is logically composed of seven areas: Enabling Layer, Spatial Data Infrastructure, OLAP Infrastructure, Storage Infrastructure, Computing Infrastructure, Analytical Infrastructure, and Registries. Each of the areas exploits several heterogeneous technologies integrating more than 500 software components. All of them are made interoperable through the exploitation of gCube Mediators while common registries make resources and data easy to discover. The publication of resources and data profiles is performed by Mediators that, in a transparent manner to the federated resources, perform harmonization and publication realizing a unified view of the infrastructure resources.
  6. Add notes from article on heterogeneous of data ....
  7. Scientific training environments: to reduce trainers’ effort in preparing platforms for practical experimentation in courses organised by universities, institutions and companies that require multidisciplinary data access, curation and analytics, e.g. Ecosystem modelling, Vessel Monitoring Systems, Fisheries Management, Biodiversity Conservation & Geospatial Data Management
  8. Add notes from article on heterogeneous of data ....
  9. Notes from article