Resource discovery in 50 words
Resource discovery is about finding pertinent answers to pertinent questions. Researchers will need to critically appraise the parameters of the question they are posing and consider the best search resource to use to find the best answers. They will need to consider whether those answers have value and whether they need to refine their question.
Resource discovery in my role
Case study 1: Assessing local inter-library loan requests
Library user requests for external resources are received on a regular basis and must be critically appraised for validity and value before proceeding. Decisions need to be taken based on a series of questions, such as:
- Does the request meet the set of criteria required to make it a valid inter-library loan request?
- Is the requester a registered user with my library?
- Is there already a version of this item accessible from Cambridge Libraries?
- Does this request contain enough valuable information to procure a set of results?
- Do I need to return to the requester to ask for more valuable data?
- Can I refine the question based on my own knowledge and experience?
Initial searches of potentially valid requests, therefore, are a quality control check. Essentially, I am searching through Cambridge holdings where positive results may invalidate the request. For this, I use the local discovery tool, iDiscover, to search for Cambridge holdings. The publication type will usually inform my search strategy.
For instance, a journal request renders better results by limiting the search to ‘journals’ and conducting a title search. Book searches produce clearer results by combining author and unique title keywords.
- Refining the search
Anomalies like grammatical errors in the reference or the catalogue record, and the language of origin must also be considered in the event of zero results. Often, changes to the journal title or edition editor names can limit or invalidate complex search results.
As this is an iterative process, the search strategy may need to be reassessed and the parameters simplified, usually yielding a greater number of hits. As a follow up, the useful range of filters available should help refine search results.
Further negative results could mean that other valuable data needs to be gathered, so a wider search engine (such as Google Scholar) or a return to the requester to gather more pertinent data may be necessary to refine the search further.
Once these internal search strategies are complete, the same strategies can be applied to search external databases for a result. There are a wide variety of useful databases to search from.
- British Library OnDemand can be used to search British Library Document Supply Centre holdings that can be specifically ordered for ILL purposes – their discovery tool will often go down to article level and account holders can place orders without delay.
- Library Hub Discover will search across multiple UK Libraries at once.
- ZETOC will search worldwide holdings for journals and conferences.
- WorldCat offers the option of searching worldwide library holdings.
Case study 2: Sourcing images for social media posts
To make social media posts more visually impactful, I often need to source form a range of suitable images.
Depending on the image style I needed, I would usually start by selecting from a range of public domain resources such as Pixabay, NASA or Unsplash.
I’d need to consider quality, size, shape and colour of the image. What message am I trying to send? Is it an appropriate image that fairly represents my audience and my library’s policy constraints?
- Refining the search
Do I need to add an additional search term to reduce the number of hits? Am I using the right keywords to find the image I am seeking or do I need to try a different approach? Do I need to use a different resource?
I’ve found the image I like, but I need to consider whether to modify it (and whether I can legally do so) to fit my intended audience. Do I need to credit the original author if I use the image?
Case study thoughts
The two case studies I have presented here have similar themes in that both searches use similar strategies where the process is both critical and iterative. Each time I conduct these types of resource discovery I find myself learning from past mistakes; understanding further which types of resource and refining search strategy accordingly to yield better results, gradually becoming more fluent and, consequently, gaining in confidence.