Get Started With Open Data: Availability, Reuse and Universal Participation
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Get Started With Open Data: Availability, Reuse and Universal Participation
- 1. Get Started With Open Data Tony Hirst Dept of Communication and Systems, The Open University
- 2. So what do we mean by “OPEN DATA”
- 4. You are free to: - copy, publish, distribute and transmit the Information; - adapt the Information; - exploit the Information commercially for example, by combining it with other Information, or by including it in your own product or application
- 5. You must: - acknowledge the source of the Information by including any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence; - ensure that you do not use the Information in a way that suggests any official status; - ensure that you do not mislead others or misrepresent the Information or its source; - ensure that your use of the Information does not breach the Data Protection Act 1998 or the Privacy and Electronic Communications (EC Directive) Regs 2003.
- 6. Exemptions: - personal data; - Information that has neither been published nor disclosed under information access legislation (FOI) by or with the consent of the Information Provider; - departmental or public sector organisation logos, crests etc; - third party rights the Information Provider is not authorised to license; - Information subject to other IPR
- 7. Availability and Access Reuse and Redistribution Universal Participation The Open Knowledge Foundation
- 8. Availability and Access: the data must be available as a whole and at no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form. The Open Knowledge Foundation
- 9. Reuse and Redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets. The Open Knowledge Foundation
- 10. Universal Participation: everyone must be able to use, reuse and redistribute – there should be no discrimination against fields of endeavour or against persons or groups. For example, ‘non-commercial’ restrictions that would prevent ‘commercial’ use, or restrictions of use for certain purposes (e.g. only in education), are not allowed. The Open Knowledge Foundation
- 12. FOI Licensing exemptions Data Paywalls protection Act Authentication DATA “Privacy” Crappy Closed spreadsheets standards PDFs Messy Data
- 15. Right to access data
- 22. So where’s the data?
- 29. “First” generation: data catalogues
- 30. Breathing life into data…
- 32. the spreadsheet becomes A DATABASE
- 36. “Second” generation: data management systems
- 38. Digging for data…
- 40. There’s lots more data that’s locked up in web pages…
- 41. Scraping…
- 42. “grabbing web content in a machine readable format and then processing it for your own purposes”
- 43. Original Extract Accessible HTML web Information web page page -> data
- 47. Recreating the database that was used to populate a (templated) page
- 52. “Creating” Data
- 56. Company Director Director Director Director Company Company Company Company
- 58. Barriers to Use
- 63. - Character string dates - Erratic whitespace - Arbitrary separators - Excel Dates Also: - month overflows at week end - year overflows
- 67. Open is as open does… DATA
Notes de l'éditeur
- A great example of timely data is data relating to roadworks. This data is often released in an impenetrable form, screeds of text detailing roadnames nobody uses and identifying in arcane language where roadworks are to take place, and what diversions have been put in place. Why is it so hard to just publish the data as KML that can be rendered trivially in an online map?!
- Another example that demonstrates how CSV can be used to help data flow is demonstrated by Google Spreadsheets. The =importData formula allows a user to specify a source data URL, and pull the CSV data found at that location in to the spreadsheet. Unlike Many Eyes Wikified, if the source data at the URL is updated, the updated will (eventually) be pulled into the spreadsheet automatically.
- One of the really good reasons for getting data into a data processing environment such as a spreadsheet is that you can start to work it. In the case of Google Spreadsheets, the spreadsheet environment can also be used as a database environment. That is, we can treat one or more data containing sheets in a spreadsheet as a database, and generate new views over the data, as well as running queries over that data.
- Another way of using a Google Spreadsheet as a database is via the Google Spreadsheets API. The GoogleVisualisation API (?) provides a way of passing queries written using the Google ???viz query language from an arbitrary web page or web application, and receiving the resulting data in a standard JSON based format, which also happens to play nicely with the Google Visualisation API???The Guardian Datastore explorer is a crude demonstration for 2009(??) demonstrating how data from the Guardian datastore, data that is stored across a range of Google spreadsheets, can be explored , queried and visualised via these APIs. Users can select a dataset from a drop down menu, fed from a delicious account to which various datastore spreadsheets have been bookmarked using a particular set of tags, or by pasting in the URL of an arbitrary (public) Google spreadsheet. The first row/headings of the data can then be previewed (a simple spreadsheet is assumed, in which column headings appear In the first row of the spreadsheet).
- A series of list boxes are then populated with the column labels and there names, and provide a certain amount of help for the creation of a query over the spreadsheet data. A range of output formats can also be selected, from simple HTML data tables, to a range of charts. URLs are also generated for HTML and CSV representations of the data returned from the query.
- One of the nice things about the data table widget (a standard GoogleVisualisation API component in this case, though similar examples exist for YUI, the Yahoo User Interface Libraries, or frameworks such as JQuery), is that is supports things like row sorting by column, (for free – no programming required!), allowing even further manipulation of the data, albeit at a simplistic level.(It’s probably worth pointing out here that it may be worth providing a preview of the column headings and first few rows (or a sample of random rows) of data when datasets are published, just so that users can see what sort of data is on offer without having to download the whole data set?)
- If you’re in the business of selling information as data, you are under threat where that information is published in an openly licensed way.
- Do we have a hashtag for the workshop?