What is Open Data?
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share

What is Open Data?

  • 561 views
Uploaded on

A very brief intro to Open Data metrics

A very brief intro to Open Data metrics

More in: Education , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
561
On Slideshare
559
From Embeds
2
Number of Embeds
1

Actions

Shares
Downloads
15
Comments
0
Likes
0

Embeds 2

http://www.linkedin.com 2

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Open Data Digital Arts and Humanities MA UCC • 12 November 2013
  • 2. What is Open Data? Open data is data that can be freely used, reused and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike. Source: The Open Definition, The Open Data Handbook
  • 3. Why Open Access? ‣ ‣ ‣ Interoperability Mashups Create New Knowledge
  • 4. What Isn’t Open? ‣ The key point is that when opening up data, the focus is on non-personal data, that is, data which does not contain information about specific individuals. ! ‣ Similarly, for some kinds of government data, national security restrictions may apply.
  • 5. Attributes of Open Data
  • 6. Tim Berners-Lee on Open Data Usage
  • 7. Open Access "The work shall be available as a whole and at no more than a reasonable reproduction cost, preferably downloading via the Internet without charge. The work must also be available in a convenient and modifiable form." ! ‣ ‣ ‣ Available as a Whole - not the limitation of indirect means; Social Openess - not merely allowed to, but you can actually get it; Machine Readable and Not Merely Human Readable
  • 8. Redistributable The license shall not restrict any party from selling or giving away the work either on its own or as part of a package made from works from many different sources. The license shall not require a royalty or other fee for such sale or distribution.
  • 9. Reuse ‣ ‣ The license must allow for modifications and derivative works and must allow them to be distributed under the terms of the original work. This does not restrict use of 'share-alike'
  • 10. Absence of Technological Restriction ‣ The work must be provided in such a form that there are no technological obstacles to the performance of the above activities. This can be achieved by the provision of the work in an open data format, i.e. one whose specification is publicly and freely available and which places no restrictions monetary or otherwise upon its use.
  • 11. Attribution ‣ The license may require as a condition for redistribution and re-use the attribution of the contributors and creators to the work. If this condition is imposed it must not be onerous. For example if attribution is required a list of those requiring attribution should accompany the work.
  • 12. Integrity ‣ The license may require as a condition for the work being distributed in modified form that the resulting work carry a different name or version number from the original work.
  • 13. No Discrimination Against Persons or Groups ‣ ‣ The license must not discriminate against any person or group of persons; Object: get the maximum benefit from the process, the maximum diversity of persons and groups should be equally eligible to contribute to open knowledge.
  • 14. No Discrimination Against Fields of Endeavour ‣ ‣ The license must not restrict anyone from making use of the work in a specific field of endeavor. For example, it may not restrict the work from being used in a business, or from being used for genetic research; Objective: Encourgae commercial users to join our community, not feel excluded from it.
  • 15. Distribution of License ‣ ‣ The rights attached to the work must apply to all to whom it is redistributed without the need for execution of an additional license by those parties; Objective: This clause is intended to forbid closing up knowledge by indirect means such as requiring a nondisclosure agreement.
  • 16. How to Open Data ‣ ‣ ‣ Keep it Simple Engage Early and Engage Often Address Common Fears and Misunderstandings
  • 17. Keep it Simple ‣ ‣ ‣ ‣ Start out small, simple and fast. There is no requirement that every dataset must be made open right now. Starting out by opening up just one dataset, or even one part of a large dataset, is fine – of course, the more datasets you can open up the better. Remember this is about innovation. Moving as rapidly as possible is good because it means you can build momentum and learn from experience – innovation is as much about failure as success and not every dataset will be useful.
  • 18. Engage Early and Engage Often ‣ ‣ ‣ ‣ ‣ Engage with actual and potential users and reusers of the data as early and as often as you can, be they citizens, businesses or developers. This will ensure that the next iteration of your service is as relevant as it can be. Much of the data will not reach ultimate users directly, but rather via ‘info-mediaries’. These are the people or services that take data and transform or remix it to be presented. For example, most of us don’t want or need a large database of GPS coordinates, we would much prefer a map. Thus, engage with infomediaries first. They will reuse and repurpose the material.
  • 19. Address Common Fears and Misconceptions ‣ ‣ This is especially important if you are working with or within educational institutions and government. When opening up data you will encounter plenty of questions and fears. It is important to ‣ ‣ (a) identify the most important ones and (b) address them at as early a stage as possible.
  • 20. Data Opening Steps ‣ ‣ ‣ ‣ Choose Your Dataset; Apply and Open License; Make the Data Available; Make it Discoverable.
  • 21. 1 Choose Your Dataset ‣ ‣ Choose the dataset(s) you plan to make open. Keep in mind that you can (and may need to) return to this step if you encounter problems at a later stage. ! ‣ ‣ ‣ Ask potential users - survey, publish intent, mailing lists, forums, etc.; Make submission easy; Learn from peers.
  • 22. 2 Apply an Open License ‣ Why License? ‣ Sake of clarity; ‣ Ensure that it is kept open. ! ‣ ‣ ‣ ‣ Creative Commons CCZero (CC0) - Dedicated to Public Domain Open Data Commons Public Domain Dedication and Licence (PDDL) - Dedicated to Public Domain - All rights waived Creative Commons Attribution (CC-BY) - Content Open Data Commons Attribution License (ODC-BY) - Data
  • 23. 3 Make the Data Available ‣ ‣ ‣ ‣ In bulk and in a useful format; You may also wish to consider alternative ways of making it available such as via an API; Consider Formats; Consider Platforms - More Later.
  • 24. 4 Make it Discoverable ‣ ‣ ‣ Post on the web and perhaps organize a central catalogue to list your open datasets; Look for Appropriate Indicies; In Ireland: ‣ ‣ Open Knowledge Foundation Ireland (http://opendata.ie) the DataHub (http://thedatahub.org/)
  • 25. 5 Star Linked Open Data 1. Available on the Web - with an open license - Open Data 2. Available as Machine-Readable Structured Data (XLS?) 3. As 2 but in a non-proprietary format (CSV vs XLS) 4. As Above but with W3C (RDF/SPARQL) to identify things 5. All above plus linked to other people’s data to provide context Source: Tim Berners-Lee, 5stardata.org
  • 26. 5 Star Linked Open Data Source: Tim Berners-Lee, 5stardata.org
  • 27. More Information ‣ ‣ ‣ Open Knowledge Foundation (http://okfn.org/) Open Data Institute (http://theodi.org/) Open Data Ireland (https://groups.google.com/forum/#! forum/open-data-ireland) ! ‣ Get Involved: ODI Meetup in Cork in January
  • 28. Thank You @iridium shawn.day@ucc.ie 2 Elderwood 1st Floor