SCIENCE MESH: �Unlocking novel modes of academia-industry collaborations

Angelo Romasanta (angelokenneth.romasanta@esade.edu)

Jonathan Wareham (jonathan.wareham@esade.edu)

ESADE Business School, Barcelona, Spain

1

This project was funded by the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No. 863353 CS3MESH4EOSC.

CACM Europe Workshop:

Collaborations and Industry

Fragmented �Landscape

2

Fragmentation

• Benefit – serve individual needs
• Problem is lack of interoperability
• the ability to seamlessly deploy, migrate and manage application workloads across different hardware and software resources from cloud providers¹
• Consequences:
• Scientific community and industry partners - Added barriers against data sharing
• IT Organizations - Vendor lock-in
• Competition in cloud - Data attracts more data. Smaller startups cannot compete
• Developers - Services cannot have wider reach

​

3

¹ Ranjan, R., “The Cloud Interoperability Challenge” IEEE Cloud Computing 1(2), 2014, pp. 20–24.

Workaround

4

5

Solution

6

Science �mesh

Science Mesh Pilot

7

Cloud vendors

Institutional �providers

Critical mass

• 300,000+ Researchers
• 10PB of data
• >1 billion files and objects

Czech Republic

Denmark

Netherlands

Poland

NRW, Germany

Switzerland

Australia

Global – CERN / Cubbit

​

Science Mesh Pilot

Federated mesh

8

Cloud vendors

Institutional �providers

Novel collaborative modes

Benefits for research

• Improve research data sharing across disciplines
• Reduce data waste
• Data is stored in silos after collection, processing and publication
• Push science
• AI systems can mine the data and assemble more powerful datasets
• Novel modes of collaboration
• Through services developed by academics and/or industry

9

Federated sharing of data

10

• Sync and share across institutional boundaries
• Enable large data transfers
• The Science Mesh enables this at a cheaper, more convenient manner

Netherlands Institute for Radio Astronomy

Astrophysics

Early adopter

Open data systems

• Convenient metadata management
• The Science Mesh can help archiving of data straight from the cloud storage interface

11

Pacific and Regional Archive for Digital Sources in Endangered Cultures

Digital Humanities

Secure collaborative apps

• Collaborative editing of documents across institutional boundaries
• Secure, no need to go to another service

12

Social Media Analytics for Society and Crisis Communication

Social Sciences

Remote data analysis

• Analyze data without transferring data through collaborative computing notebooks
• Transferring data may not be convenient. The Science Mesh enables data analysis remotely

13

EU Joint Research Centre Big Data Analytics Platform

Earth Observation

CERN

High energy physics

Summary

• Science Mesh – infrastructure that will connect various cloud providers serving scientists
• Industry:
• Can easily collaborate and leverage data from their academic counterparts
• Can develop apps to serve research needs and enable new collaborative functionalities

14

Thank you

15