Project mentors: Anja Brunner (Reaxys), Damon Ridley (Reaxys) and anyone else who would like to support the project!
At Elsevier, our searches in Reaxys are influenced by our knowledge of the content, structure and search options of our product. It is clear to us, however, that Reaxys users may approach finding information in Reaxys differently. So, we want to learn from you — users of Reaxys. How would you teach others to leverage the search capabilities of Reaxys? If you take on one of the following projects (or have an idea for another similar project), our hope is that you will explore the content and functions of Reaxys and develop some best practices or “tips and tricks” that help other users to take full advantage of what Reaxys has to offer.
OPERATORS AND TRUNCATION IN SEARCHES
Most of us know the Boolean operators AND, NOT, OR. In a search, these operators offer different ways of linking together query terms and specifying how the terms relate to the hits that result. In the same way, NEAR, NEXT and PROXIMITY help refine the input criteria for a search. Truncation also serves to optimize a search strategy, opening the possibility of finding a broader range of information connected by a steadfast commonality, such as the stem of a word. Another form of truncation is entering ? or * in a formula to be searched in Reaxys.
(1) How does Reaxys interpret operators and truncations?
(2) What is the impact of these different operators on the outcome of a search?
(3) How exactly does a hit set change depending on what operators or truncation are used?
(4) What rules can one follow in their use?
(5) How are operators implemented in other search engines/databases?
Prepare a set of screencasts to explain the role of operators and truncation in search strategies.
BUILDING AN EFFECTIVE SEARCH STRATEGY
We are all used to the ease with which we enter a phrase into Google and get relevant answers to our question. At the same time, we also know that the long list of hits that emerges includes a lot of irrelevant results and we rarely go beyond the first couple of hit pages. A search for scientific information can be quite complicated. Ideally, we build a search to retrieve only relevant hits, but at the same time ensure that the answers we get are comprehensive.
A search strategy is our approach to finding answers to a question. In a natural language search engine, that approach may be figuring out the best way to phrase our question. In a user interface like Query builder in Reaxys, that involves figuring out what type of information we are looking for, what terms should we query, and how will we connect the search fields used. Another aspect of a search strategy may be any form of processing we do with the results from a search -- like combining hit sets from 2 or more searches, filtering or analyzing hit sets.
Defining a search strategy can be difficult. it is influenced by the type of question asked, the type of search engine or system used, and the knowledge context of our question -- a search for a particular reaction can be approached in different ways depending on what we know about the reaction itself.
So how do you build a search strategy? What steps do you follow? How do you inform your approach and where to you find the right query terms to use?
Pick a question and show how you can use Reaxys to optimize your search strategy to answer the question. Just to narrow the scope of the project, focus on a specific type of search:
(1) search for information on a particular chemistry topic
(2) search for a substance or group of substances that meet certain criteria
(3) search for properties of substances that would help you identify an unknown
(4) search for a reaction and figure out how to optimize it
Use screencasts to show your thought process and the steps in generating optimal sets of answers. Based on your exploration, build guidelines you can share with others for building effective search strategies.