With a growing requirement to produce reports and briefing documents based on the information you retrieve, library and information professionals in all sectors can learn from techniques used by journalists.
Spotlight is a movie that tells the true story of how journalists at the Boston Globe lifted the lid on a major cover-up in the Catholic Church. During their investigations, the team did everything you would expect investigative journalists to do: they door-stepped people; they confronted leading figures; they waited for hours in outer offices trying to grab interviews.
But the backbone of their research was a simple spreadsheet onto which they made entries from back issues of the Massachusetts Catholic Directory. It was this that enabled them to spot the suspicious patterns of behaviour that underpinned their revelations.
This kind of activity is increasing dramatically in importance. At the rocket science end of the spectrum it’s manifesting itself as big data, where analysts develop and employ applications to trawl vast quantities of data, looking for patterns that can be turned into e-commerce or other opportunities.
But the principle of applying critical analysis to retrieved data operates across the board – including to the human brain power that we bring to bear in carrying out literature searches. Of course, we mere mortals do face limitations, mainly in the tiny amount of content we are capable of evaluating within a sensible timescale compared with what computers can achieve – but that doesn’t mean we’re incapable of doing it.
Ploughing has had its day
Turning your raw search results into a narrative report – one that enables your enquirer to reach a decision, make a recommendation or take action – is becoming the stock in trade of information professionals in a growing number of fields, including government, health services and law.
Information professionals who carry out desk research on their users’ behalf are the obvious and immediate beneficiaries of techniques such as these. But the skills are no less valuable for academic librarians, charged with fostering information literacy and encouraging good research practice in students doing assignments.
Simply ploughing through a linear list of unstructured search results, hoping that the most useful ones will pop out at you, isn’t an efficient way of going about the task. Taking our cue from those Boston Globe journalists, we can get far more out of our results by turning them into a flexible dataset.
To do this, you might be able to make use of your chosen reference management package. This should at least save you time by automating the presentation of each document’s bibliographic characteristics, and you may then be able to add extra customised fields for the further ways in which you want to arrange your search results.
You may also find that you have to add ‘grey’ literature – short reports, articles from non-mainstream sources, website content, ephemera – manually. Obviously making these manual additions could be time-consuming, but it will probably be time well invested because, once entered, the reference management software will treat these non-standard documents just the same as the others, ensuring a uniform format for every document and allowing you to create bibliographies automatically.
So if you can use a reference management package to automate at least part of the process, that should save you a great deal of time at the next stage. But if you can’t, you could use any application that will support this kind of matrix structure – a spreadsheet or database package, the table function in a word processed document, or any proprietary software that can be used for project management purposes.
You may also be able to automate some of the process by making use of the text-to-table conversion function that comes with your word processing package – although the resulting table may need so much repair that you may be no better off than if you had done the whole thing manually in the first place.
Letting you change your mind
Obviously the more you can automate the better – but whatever means you decide to use to restructure your search results, you will need to satisfy yourself that your chosen approach will enable you to:
• work with documents taken from any source you choose, not just mainstream ones
• describe those documents using whatever headings you want
• sort and re-sort the documents using multiple criteria determined by you.
What sort of criteria? Well, subject topics clearly – but you (or your student) will also need to be able to sort the documents according to how useful they’re likely to be in answering the enquiry. There’s a really good principle for ranking documents in this way: Must Know; Should Know; Could Know.
Must know documents are the handful of retrieved results that are so comprehensive and so authoritative that you’re going to use them as the basis for your report (or your student as the basis of their assignment).
Should know documents might provide evidence supporting the main findings, or include case studies demonstrating how the techniques outlined in the Must Know documents would work in practice.
Could know documents include the rest of your viable results. They’re potentially useful in terms of detail, but they’re not going to add a great deal more to your enquirer’s overall understanding of the subject.
Crucially, organising your documents in this way enables you to change your mind whenever you need to. If you find you’re now not so keen on the documents that have come to the top as Must Knows, it’s the work of minutes to rethink, re-categorise and sort again.
Get this far, and it’s only a slight exaggeration to say that your report can practically draft itself. But to complete the job, you do need to be able to deploy another key skill: strategic reading. We’ll look at that in a follow-up blog.
You can also check out Tim Buckley Owen’s blog article on what library and information professionals learn from the ‘Dodgy Dossier’.
Find out more about Tim Buckley Owen’s Successful Enquiry Answering Every Time 7th edition from Facet Publishing
Tim Buckley Owen BA DipLib MCLIP is an independent writer and trainer with over 40 years’ experience of information work – at Westminster Central Reference Library, the City Business Library, and as Principal Information Officer at the London Research Centre. He has also held strategic media and communications posts at CILIP, the Museums, Libraries & Archives Council and the Library & Information Commission.
This blog post originally appeared on the CILIP blog in April 2017. You can view the original post here: https://www.cilip.org.uk/blog/6-suggestions-teaching-information-literacy