In The Re-Birth of the “Beat”: A hyperlocal online newsgathering model (Journalism Practice 6.5-6 (2012): 754-765), Murray Dick cites various others to suggest that routine sources are responsible for generating a significant percentage of local news reports:
Schlesinger [Schlesinger, Philip (1987) Putting ‘Reality’ Together: BBC News. Taylor & Francis: London] found that BBC news was dependent on routine sources for up to 80 per cent of its output, while later [Franklin, Bob and Murphy, David (1991) Making the Local News: Local Journalism in Context. Routledge: London] established that local press relied upon local government, courts, police, business and voluntary organisations for 67 per cent of their stories (in [Keeble, Richard (2009) Ethics for Journalists, 2nd Edition. Routledge: London], p114-15)”].
As well as human sources, news gatherers may also look to data sources at either a local level, such as local council transparency (that is, spending data), or national data sources with a local scope as part of a regular beat. For example, the NHS publish accident and emergency statistics as the provider organisation level on a weekly basis, and nomis, the official labour market statistics publisher, publish unemployment figures at a local council level on a monthly basis. Ratings agencies such as the Care Quality Commission (CQC) and the Food Standards Agency (FSA) publish inspections data for local establishments as it becomes available, and other national agencies publish data annually that can be broken down to a local level: if you want to track car MOT failures at the postcode region level, the DVLA have the data that will help you do it.
To a certain extent, adding data sources to a regular beat, or making a beat purely from data sources enables the automatic generation of data driven press releases that can be used to shorten the production process of news reports about a particular class of routine stories that are essentially reports about “the latest figures” (see, for example, my nomis Labour Market Statistics textualisation sketch).
Data sources can also be used to support the newsgathering process by processing the data in order to raise alerts or bring attention to particular facts that might otherwise go unnoticed. Where the data has a numerical basis, this might relate to sorting a national dataset on the basis of some indicator value or other and highlighting to a particular local news outlet that their local X is in the top M or bottom N of similar establishments in the rest of the country, and that there may be a story there. Where the data has a text basis, looking for keywords might pull out paragraphs or records that are of particular interest, or running a text through an entity recognition engine such as Thomson Reuters’ OpenCalais might automatically help identify individuals or organisations of interest.
In this context of this post, I will be considering the role that metadata about court cases that is contained within court lists and court registers might have to play in helping news media identify possibly newsworthy stories arising from court proceedings. I will also explore the extent to which the metadata may be processed, both in order to help identify court proceedings that may be worth reporting on, as well to produce statistical summaries that may in themselves be newsworthy and provide a more balanced view over the activity of the courts than the impression one might get about their behaviour simply from the balance of coverage provided by the media.