Some of the information you'll need for university won't be accessible to you if you rely on Google. Instead, you may need to access special databases to find what you need.
A lot of databases look like websites, and so we expect them to behave a lot like Google. But this just isn’t the case. Databases have a language of their own, and they won't typically understand what you're looking for if you treat them like Google search. However, if you take the time to speak the language of databases, you are much more likely to get what you need from them quickly.
There are some simple techniques you can learn to enhance your database searching, which should improve the quality and relevance of your results.
The simple words AND or OR can be inserted into your search to help you tell the database what you really need. These words are known as ‘connectors’ (or operators), as they connect your keywords together in a logical way so that the database interprets what you need more effectively.
Watch the short video below [6:30 minutes] to learn more.
Using the OR connector in your search should give you more results.
Using the AND connector in your search should give you fewer results.
Using the AND and OR connectors together in your search could give you precise results.
There’s also an option to use NOT to limit your search results. However, you should only use this connector if you are sure that you will not inadvertently eliminate information that could be, in fact, very useful.
If you need to search for a recognised phrase (a phrase is two words or more) there is a technique that you can try that clarifies what you need.
For example, if you type in the keywords mental health, the algorithm will search for any resource that mentions ‘mental health’, but also resources that mention ‘mental’, as well any resources that mention ‘health’. You may get some relevant results, but you will get thousands of irrelevant results as well (such as mental arithmetic or public health or health visitor etc).
Instead, by using double speech marks around the phrase “mental health”, you can force the algorithm to recognise those words together as a key phrase. This should reduce the number of results you get whilst improving the relevancy.
Here are two techniques that are similar, which you can try to save time and maximise potential results. These techniques both instruct the database to search for different forms of a word simultaneously.
Imagine that you are broadly interested in psychology and interested in comparing the work that psychologists, psychiatrists and psychotherapists do. Instead of typing in all these keywords, you could try typing in the shared letters (e.g., psych) and then adding an asterisk (*) symbol: psych*
This technique instructs the database to search for any words that begin with those letters.
You will get results that include these keywords: psychology, psychologists, psychiatrists, psychiatry, psychotherapy, psychodynamic, psychedelic, psychopathology, psychic etc.
Although some of those words might not be what you intended, they could still guide you towards information that you didn’t realise was relevant.
The ‘wildcard’ techniques are similar. Essentially, you can try this trick if you are not sure how a keyword is spelt. Just insert an exclamation mark (!) or a question mark (?) or a hashtag (#) to replace the letter(s) you are unsure of.
Truncation and wildcards are useful when you want to broaden your search and retrieve more results. You can also combine these techniques with other techniques in this section.
Proximity searching is a technique used to find resources where two or more relevant words are situated within a certain distance of each other in the text of a book or article. This technique is useful when you want to find documents that contain phrases or concepts that are related to each other.
For example, if you search for:
you will get results for resources that contain the word ‘pet’ within six words of the word ‘therapy’.
You could try adding truncation:
you will get results for resources that contain the word ‘pet’ within six words of the words ‘therapy’, ‘therapies’, ‘therapists’, ‘therapeutic’ etc.
Once you have performed a search in a database, you should see a list of results. Next, you usually have the option to filter the results by using ‘limiters’. This technique helps you reduce the number of results whilst increasing their relevancy.
The most successful limiters are:
When you search for keywords, the database will usually search as broadly as possible; it will search for your keywords anywhere in the resource: the title, abstract, and even the full text. Sometimes this can be too broad, though, and you might get results that don’t really ‘hit’ what you need.
You can adjust your search parameters to only find keywords in certain parts of the source, these are known as ‘fields’. The most popular fields are title, author, abstract, or subject.
For example, if you know the precise author of a book, you could instruct the database to search in the ‘Author’ field. Similarly, if you know the title of an article, you could instruct the database to search in the ‘Title’ field. The ‘abstract’ field can be really useful as well, if you are using all the right keywords and search techniques but still getting too many results.
The best thing to do is to practice using different databases so that you get more used to what works well for your needs.
It’s possible to use some, or all, of these techniques in combination to improve your database searches.
Watch the video below [3.43 minutes) to see this in action.