Theme: Information Systems

This is a compulsory session which introduces new graduate students to the Department of Chemistry Library and its place within the wider Cambridge University Library system. It provides general information on what is available, where it is, and how to get it. Print and online resources are included.

You must choose one session out of the 9 sessions available.

A ‘recommended’ optional course for Chemistry graduates that introduces all the relevant online databases available to you in the university: citation databases such as Web of Science, Scopus, and PubMed, which index all the scientific literature that is published, as well as chemistry and related subject-specific databases. You will be guided on how to search citation databases effectively and the session includes a hands-on element where you can practice - please bring your own laptop.

The session will be most suitable for those who are new to searching citation databases or would like a refresher.

Please note that this session will not cover searching the databases Reaxys and SciFinder. These are covered by IS5.

• Please bring your own laptop so you can participate in the practical element of the session

This compulsory course will equip you with the skills required to manage the research information you will need to gather throughout your graduate course, as well as the publications you will produce yourself. It will also help you enhance your online research profile and measure the impact of research.

This compulsory session introduces Research Data Management (RDM) to Chemistry PhD students. It is highly interactive and utilises practical activities throughout.

Key topics covered are:

• Research Data Management (RDM) - what it is and what problems can occur with managing and sharing your data.
• Data backup and file sharing - possible consequences of not backing up your data, strategies for backing up your data and sharing your data safely.
• Data organisation - how to organise your files and folders, what is best practice.
• Data sharing - obstacles to sharing your data, benefits and importance of sharing your data, the funder policy landscape, resources available in the University to help you share your data.
• Data management planning - creating a roadmap for how not to get lost in your data!

Lunch and refreshments are included for this course

A ‘highly recommended’ optional course introducing electronic databases SciFinder and Reaxys presented by Professor Jonathan Goodman comprising of presentation followed by hands-on investigation.

SciFinder https://www.cas.org/products/scifinder provides access to biochemical, chemical, chemical engineering, medical and other related information in journal and patent literature. Bibliographic, substance and reaction information is available. SciFinder includes references from more than 10,000 scientific journals and patent information from 63 patent issuing authorities. Sources include journals, patents, conference proceedings, dissertations, technical reports and books. It is one of the world’s largest collections of organic and inorganic substance information.

It is possible to search by topic, author, company name, chemical structure, substructure, structure similarity and reaction. Personal registration is required for access to SciFinder on- and off-campus, please follow the instructions at: https://www-library.ch.cam.ac.uk/scifinder

Reaxys combines the content of CrossFire Beilstein, Gmelin and the Patent Chemistry Database in one search. Validated reaction and substance data are integrated with synthesis planning. Data from all three sources are merged into one substance record. Unlimited access on-campus via the web: https://www.reaxys.com/. Off-campus access via Raven password. (Personal registration is not required for access).

Please see the prerequisites. Please bring your own laptop for the practical element of the session.

Research reproducibility can be hard to get right. The aim of this talk is to raise awareness on the common pitfalls so you can confidently share your work for posterity. We will cover the dos and don’ts of data processing, how to comment on a script, and how to share it. Python will be used as an example because a variety of tools exist for this language. The goal is for anyone reading your paper to be able to go from the raw data to your paper figures.

The talk will last 20 minutes and there will be time for questions/discussion afterwards.

This talk is brought to you by the Chemistry Data Champions https://www-library.ch.cam.ac.uk/chemistry-data-champions