An introduction to Data Journalism

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Presentation at School of Data training on May 14th for journalists at training with Open Data PH Taskforce in the Philippines.

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<ul><li> Data journalism - setting the stage Anders Pedersen @anpe @SchoolOfData </li> <li> Open Knowledge Open Knowledge is a worldwide non-profit network of people passionate about openness, using advocacy, technology and training to unlock information and enable people to work with it to create and share knowledge. </li> <li> Evidence is power School of Data works to empower civil society organizations, journalists and citizens with the skills they need to use data effectively in their effort to create better societies. </li> <li> Target audience We work mostly with change makers: NGOs and journalists. We empower them to use data effectively to advance their cause and mission through a combination of training and long terms support. </li> <li> Why School of Data School of Data is a critical component of the open data ecosystem: provides tools and training to empower people to use open data for good - especially to people new to open data; supports outreach and engagement by creating a supportive community of learners and mentors - working with Open Knowledge Foundation Local Groups; creates opportunities for people and communities to use open data to make an impact; works both with governments to open up data and data users such as journalists and NGOs. </li> <li> Slide name here Data expeditions - online and offline short gatherings where a group of people with different backgrounds tackle a data related problem Data clinics - hands on support working directly with peoples data Mentoring - local mentors working with local communities Online content - tutorial and walkthroughs Offline resources e.g. Data Journalism Handbook </li> <li> Slide name here We work globally, with a focus on the following regions: Latin America, Sub Saharan Africa and Middle East, Europe School of Data is translated in Spanish and Portuguese Future: French, Greek and Italian Over 10 fellows working in countries like: Egypt, Lebanon, Uganda, Mexico, Costa Rica, Brazil, etc. </li> <li> Data Journalism: Setting the stage </li> <li> Where do gun owners live? Complex stories can now be told </li> <li> Budget information that readers can understand But be aware of complexity! </li> <li> How quickly will the ambulance arrive? Source: http://visualoop.com/media/2012/11/How-fast-is-LAFD- where-you-live-750x298.jpg Enables you to focus locally </li> <li> And how about the fire truck? Fire fighter response times in London </li> <li> Granularity is king Tip: the story is almost always buried in granular data Source: Mapumental </li> <li> Granularity is king Who benefits from government subsidies? </li> <li> Who are benefiting from government contracts? Source: http://usual-suppliers.pudo.org/ </li> <li> Data journalism is also text mining U.K. MP expenses 700,000 documents in PDF- format Wikileaks Iraq war data 391,832 structured records, each including a text descriptions Wikileaks diplomatic cables 251,287 cables, each a few pages long NSA files leaked by Snowden 50,000 to 200,000 according to the NSA A text document also contains data Source: Jonathan Stray, Overview project </li> <li> Telling clear stories Where do companies live? </li> <li> Company ownership networks </li> <li> Where do people live? Source: Where nobody lives, http://mapsbynik.tumblr.com/post/82791188950/nobody-lives-here-the- nearly-5-million-census Demographics: Where nobody lives </li> <li> Using statistics can help you find stories Stories in statistics: regression analysis and outliers test fraud cases </li> <li> Condition: Machine readable data Nothing beats a good CSV file </li> <li> Good data is rarely available </li> <li> How we often get important data Government official: Please receive our annual audit reports in this stack of papers. Hard copies = hard work! </li> <li> Crowd cleaning of data When data is messy: Readers can assist extracting and cleaning data </li> <li> Crowd cleaning of data Readers can annotate documents </li> <li> Mapping people, power and money Source: Who is in charge created by CIVIO (Spain), http://quienmanda.es/ Mapping relationships </li> <li> Who are friending who? What is in a picture? Matching faces to names Source: vg.no mapping the royal family network in Norway (left), Dirty Energy Money (right) </li> <li> Connected China Source: Who is in charge created by CIVIO (Spain), http://quienmanda.es/ Data on relationships </li> <li> Crowd collection of data Readers can assist collecting data </li> <li> A clear bar chart is often all you need </li> <li> Spending: make readers understand </li> <li> Where to find the data? </li> <li> The data journalism tool box Extraction and scraping Tabula Scraperwiki Online OCR Data cleaning Open Refine Spreadsheets - yes, you cannot live without Visualisation DataWrapper - http://datawrapper.de/ D3.js - http://d3js.org/ The Data Journalism Handbook School of Data The tools you need </li> <li> The data journalism tool box Extraction and scraping Tabula Scraperwiki Online OCR Data cleaning Open Refine Spreadsheets - yes, you cannot live without Visualisation DataWrapper - http://datawrapper.de/ D3.js - http://d3js.org/ The Data Journalism Handbook School of Data The tools you need </li> <li> Mailing lists </li> <li> Thank you! Stay in touch: anders.pedersen@okfn.org | schoolofdata@okfn.org @anpe | @SchooOfData </li> </ul>