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Best Practice: Support Open Data Start Ups

27 June 2016

This version
http://www.w3.org/2013/share-psi/bp/su-20160627/
Latest version
http://www.w3.org/2013/share-psi/bp/su/
Previous version
http://www.w3.org/2013/share-psi/bp/su-20160404/

This is one of a set of Best Practices developed by the Share-PSI 2.0 Thematic Network.

Creative Commons Licence Share-PSI Best Practice: Support Open Data Start Ups by Share-PSI 2.0 is licensed under a Creative Commons Attribution 4.0 International License.


Outline

An academic business accelerator is an organisational unit within a university that aims to mobilise and support people to build their own enterprise. The unit is responsible for transferring the innovation and entrepreneurship mentality to the next generation of skilled entrepreneurs. It also maintains collaboration with private and public structures for funding and mentoring. Open data can provide a very useful basis for entrepreneurship, allowing for development of added value services by citizens and small enterprises. The open data sub-unit enhances the collaboration between universities (potential entrepreneurs) with private and public funding organisations (chambers of commerce, municipalities, start-up investors) and experts (coaches and mentors) from the private sector in order to foster innovative open data start-ups to go live.

Challenge

Getting a PSI / open data inspired based business up and running requires a multitude of fields of knowledge and mentoring.

Solution

Universities are well inter-connected, they have the required knowledge necessary for open data startups like (statisitics, visualisation, programming), and they usually have the necessary relationships to practitioners, and other academics to complete missing skills and knwoledge.

Furthermore they can provide:

  • Resources: They often own facilities which are not used upto their full capacity.
  • Mentoring: University nodes can act as a trusted third party intermediary, who can establish the first contacts, or bring the first 5 customers.
  • Networking to startups: Professors, Professionals.
  • Potential Entrepreneurs like students, Alumni, SMEs, Individuals.

Why is this a Best Practice?

It contributes to sustainable growth and entrepreneurship based on Open Data, in Europe.

Why is this a Best Practice?

It contributes to sustainable growth and entrepreneurship based on Open Data, in Europe.

How do I implement this Best Practice?

A new structure in a University or other similar educational institute is needed.

Detailed steps towards the academic startup incubator:

  • make open data via web services available to students: provide some initial tools, training, technology groups;
  • expand on successful startup examples, generalize and apply to other areas of business;
  • make long lasting competitions, as one month is not enough in order to distill ideas;
  • connect with the outer world: journalists;
  • provide legal advice for the establishment, IPR and privacy;
  • mentors should also come from successful startups;
  • The loudest bird survives: Blog on every activity, involve students into that process;
  • team up with another academic school (unite media and technics);
  • provide intercultural communication education, as startups are likely to provide services on an international scale;
  • first identify friendly customers, then make them enthusiasts.

Where has this best practice been implemented?

Country Implementation Contact Point
Greece The University of the Aegean Startup Incubator Yannis Charalabidis, University of the Aegean
Greece Gov4All platform: University of the Aegean/Microsoft Greece open data incubator Yannis Charalabidis, University of the Aegean
Australia DataStart: A public-private partnership Tim Neal, Data Policy, Department of the Prime Minister and Cabinet, Australia
Czech Republic Fond Otakara Motejla motejl@motejl.cz
Spain Gijón OpenDataLab: local start-up incubator Martin Alvarez-Espinar, CTIC

References

Contact Info

Yannis Charalabidis, University of the Aegean.

Issue Tracker

Any matters arising from this BP, including implementation experience, lessons learnt, places where it has been implemented or guides that cite this BP can be recorded and discussed on the project's GitHub repository

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