module specification

This module will further the students’ expertise in online data analysis and gathering. The open data movement in the UK and internationally is seeing a continual release of newsworthy data: datasets are released by regulators, consumer groups, charities, scientific institutions and businesses.  Freedom of Information requests are logged on What Do They Know, as well as on organisations' own disclosure logs. The Guardian's datablog is a pioneering journalistic example.

Journalists , however, also need to ask questions. This module will combine teaching the technical skills and tools – including some codes and programs - needed to access datasets with the critical questioning needed to develop stories. Such developments will necessitate contextualising initial data with further data – eg, Government employment figures with demographic information.

Some programming knowledge will be useful, as well skills with graphics, but the main aim of the course will be to liberate data from closed databases into the bright light of media audiences.

The module will be assessed by a timed in-class assessment, a portfolio consisting of two pieces from different media and a self-assessed grid, moderated by tutors at the end of the teaching period.

The module’s aims are:

• An understanding of the professional techniques and processes involved in database building and analysis, including ethical issues;
• Opportunity to work singly and collaboratively in developing data-originated stories, both to set briefs and originally;
• Development of transferable skills needed to produce content for different media, including broadcast, text, audio and web;
• Creation of original journalism for different platforms, adding to employability portfolio.
• Analysis of skills and techniques needed to communicate stories effectively.

Students will develop an understanding of how best to forge ideas from data – online, audio, video --
and how best to exploit each technical set of competencies, singly and as complements.

Facts are sacred: but where do we find them? Journalists have to balance their role in responding to events with their role as an active seeker of stories - and data is no different. The New York Times' Aron Pilhofer recommends that you "Start small, and start with something you already know and already do. And always, always, always remember that the goal here is journalism." The Guardian's Charles Arthur suggests "Find a story that will be best told through numbers".
Since data journalism represents the convergence of a number of fields which are significant in their own right - from investigative research and statistics to design and programming –it crosses the fields of digital media and journalism. The idea of combining those skills to tell important stories is powerful - but also intimidating.

The course will outline four areas:

1. Finding data
   Finding data' can involve anything from having expert knowledge and contacts to being able to use computer assisted reporting skills or, for some, specific technical skills such as MySQL or Python to gather the data for you. Here APIs (automated programming interfaces) come into their own.
2. Interrogating data
   Interrogating data well means you need to have a good understanding of jargon and the wider context within which data sits, plus statistics - a familiarity with spreadsheets can help save a lot of time.
3. Visualising data
   Visualising and mashing data has historically been the responsibility of designers and coders, but an increasing number of people with editorial backgrounds are trying their hand at both - partly because of a widening awareness of what is possible, and partly because of a lowering of the barriers to experimenting with them.
4. Mashing data
5. Tools such as ManyEyes for visualisation, and Yahoo! Pipes for mashups, have made it possible for journalism students to engage quickly with the possibilities.

But there are ethical considerations. Infographics can easily lose origins and be plagiarized. And what data should be made public? Classes will consider issues of security and copyright, such controversies as WikiLeaks and tax exiles and monetization of data.

Journalists will produce work using the tools for the first assignment, which will be marked on proficiency in techniques. For the second assignment, they will produce a story with an eye to the market and to breaking news.

Learning and teaching strategy will be based on an interactive model.
For most of the 15 teaching weeks, a three-hourly session will require students to to work with each other and individually on technical and newsgathering tasks.
They will also need to create their own recording techniques, devise their preferred visualisations, present independent research and ideas and contest information presented by staff and other students.
Their final portfolios will display professional skills learned in class.
In enhancement weeks, newsdays will allow a virtual professional environment to foster team-building and employability. Feedback will be given one-to-one, in class and electronically on the class wiki.
Working in small teams will develop students’ social as well as academic skills.
The module will be supported by a VLE site containing notes, readings and extended bibliographies, and weblinks.
Opportunities for pdp will be supported through the whole course.

Students who read all the required texts, participate in all the class activities and complete the required assessments and assignments, should be able to:

• Utilise the techniques and tools required for data news gathering and writing to a professionally acceptable level, working singly and collaboratively;
• Write to length and to brief, working within different media and for different effects, creating a portfolio of work;
• Analyse, develop and use in practice the data analysis skills needed to develop stories from a variety of sources, including recording, visualising  and mashing up;
• Present and originate stories in different formats and different modes;
• Reflect upon and be able to explain the rationale for technical, ethical and professional choices.

• Formative assessment will comprise short exercises and presentations to seminars and workshops. Formative feedback will also be given on draft portfolio items.
• Summative assessment will comprise: one portfolio consisting of two pieces demonstrating data skills and story construction, a timed in-class assessment demonstrating data skills and moderation by tutors of self-assessed contribution in class, monitored through a class wiki.
• The timed assessment will involve a data scraping exercise which must then be realised in a journalistically acceptable format, involving visualising and writing.
• The portfolio will contain two stories based on published data. The stories must be original, written in clear English and with at least two visual elements, like tables, maps, graphics or graphs. They can complement each other or contrast.

Free online tools
http://www.mysql.com/
http://www.python.org/getit/
http://www-958.ibm.com/software/data/cognos/manyeyes/
http://pipes.yahoo.com/pipes/
www.openheatmap.com
http://www.tableausoftware.com/public
http://www.freebase.com/labs/gridworks

Paid for:
http://www.outwit.com/

Websites:
http://helpmeinvestigate.com/
www.guardian.co.uk
www.whatdotheyknow.com
www.ico.gov.uk
flickr
http://www.guardian.co.uk/world-government-data