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The challenge As noted in Open Data Stories’ first story, there are calls from various quarters for more data on the utility of governments releasing data and other material for re-use. The challenge would seem to be this: if people and organisations want governments to continue to invest in open data initiatives, they should jump into the feedback loop and tell governments, and the world, when they are putting open government data to good use. The scale or nature of beneficial use shouldn’t matter. It might be economic, creative, cultural or environmental. Or it could be something else. But tell us your story. Equally, interested stakeholders such as Creative Commons, the Open Knowledge Foundation and the Sunlight Foundation can tell us their stories too, even if that is only drawing us to relevant (and openly licensed ) articles that we can repost on Open Data Stories. And, of course, agencies who see the data they steward being put to good use should tell us too. Whatever the case, share your stories with others. The more you do, the richer the feedback loop and that, in turn, is likely to enable open data policies to be better developed and refined and, ultimately, to be sustainable.

The Open Data Handbook¶ This handbook discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to open up data. It discusses the why, what and how of open data – why to go open, what open is, and the how to ‘open’ data. To get started, you may wish to look at the Introduction. You can navigate through the report using the Table of Contents (see sidebar or below). We warmly welcome comments on the text and will incorporate feedback as we go forward. We also welcome contributions or suggestions for additional sections and areas to examine.

The Open Data Handbook¶ This handbook discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to open up data. It discusses the why, what and how of open data – why to go open, what open is, and the how to ‘open’ data. To get started, you may wish to look at the Introduction. You can navigate through the report using the Table of Contents (see sidebar or below). We warmly welcome comments on the text and will incorporate feedback as we go forward. We also welcome contributions or suggestions for additional sections and areas to examine.

SchemaSpyGraphical Database Schema Metadata Browser Sample Output FAQ Download Release Notes Support SchemaSpy John Currier Recent Donors: Anonymous monocongo chervitz Do you hate starting on a new project and having to try to figure out someone else's idea of a database? Or are you in QA and the developers expect you to understand all the relationships in their schema? If so then this tool's for you. SchemaSpy is a Java-based tool (requires Java 5 or higher) that analyzes the metadata of a schema in a database and generates a visual representation of it in a browser-displayable format. It lets you click through the hierarchy of database tables via child and parent table relationships as represented by both HTML links and entity-relationship diagrams. It's also designed to help resolve the obtuse errors that a database sometimes gives related to failures due to constraints.

Using Overview to analyze 4500 pages of documents on security contractors in Iraq by Jonathan Stray on 02/21/2012 0 This post describes how we used a prototype of the Overview software to explore 4,500 pages of incident reports concerning the actions of private security contractors working for the U.S. State Department during the Iraq war. This was the core of the reporting work for our previous post, where we reported the results of that analysis. The promise of a document set like this is that it will give us some idea of the broader picture, beyond the handful of really egregious incidents that have made headlines. To do this, in some way we have to take into account most or all of the documents, not just the small number that might match a particular keyword search.  But at one page per minute, eight hours per day, it would take about 10 days for one person to read all of these documents — to say nothing of taking notes or doing any sort of followup. This is exactly the sort of problem that Overview would like to solve. The reporting was a multi-stage process: Splitting the massive PDFs into individual documents and extracting the text Exploration and subject tagging with the Overview prototype Random sampling to estimate the frequency of certain types of events Followup and comparison with other sources