Theme: Research Data Management

The nature of research is changing. What is the potential of text & data mining (TDM)to impact on this? How are researchers today using TDM to cope with the ever-increasing amount of information available? Are funder and publisher policies adapting to reflect both the legal right UK researcher have to mine published literature and the new possibilities TDM now present? These are some of the questions we will be asking in this day of talks, workshops and discussions.

Join plenary speaker Kiera McNeice of the FutureTDM project, Cambridge researchers and the National Centre for Text Mining, along with guest speakers from UCL, PLOS and more to discover:

• practical tips for TDM
• what TDM tools are available
• advice on supporting researchers using, or considering using, TDM
• improving the quality of research through TDM
• innovations in TDM – new uses for technologies in research

Coffee and lunch will be provided and the day will end with a summer drinks reception.

There is a charge for this event. These charges are:

• £10 for University of Cambridge members
• £50 for all other attendees

Once you have booked your place here, please follow this link to make your payment: http://onlinesales.admin.cam.ac.uk/conferences-and-events/university-library/text-data-mining-symposium/text-data-mining-symposium

Can't make the symposium? Watch the opening Plenary and closing roundtable discussions via live-stream from 11:00 on Wednesday 12 July by following this link: http://cam.adobeconnect.com/osc2/ Simply select to 'Enter as Guest' (no need to create an Adobe Connect account).

You can also catch up when the recordings are available on the Office of Scholarly Communication 'Recordings of Past Events' page: http://osc.cam.ac.uk/events/recordings-past-events

A program for the day can be found here: https://docs.google.com/document/d/1l4N2fSFgpL3iMbjKC3IxHz7GpNVvERB5NzxqWp8jZQo/edit?usp=sharing

David Carr and Robert Kiley from the Wellcome Trust are coming to Cambridge to talk with researchers about the Trust’s policy on data, software and materials management and sharing, which was released in July 2017. They will give short talks about the extended requirements for sharing all research outputs and an update on how their policy on open research has been working. Afterwards you will have the opportunity to ask them any questions you might have.

This event will be held in the Gurdon Institute tea-room.

Librarians are used to dealing with data in all its forms but sometimes researchers aren't so sure. Many funders now require evidence from the researcher of how they plan to manage the data they use and collect during the research process and this often has to be tailored to specific guidelines. This presents a great opportunity for library staff to work with the research community but how do they get started?

Join the OSC to learn more about what a data management plan is, why they are necessary, the different information needed, how to complete one and how to support someone in completing theirs. This interactive train-the-trainer workshop will include a mix of presentations and activities with a chance to put your new knowledge into practice.

Prevent research disasters through good data management

• How much information would you lose if your laptop was stolen?
• Have you ever emailed your colleague a file named 'final_final_versionEDITED'?
• Do you know what your funder expects you to do with your research information?

As a researcher, you will encounter research data in many forms, ranging from literature sources, interviews, measurements, numbers and images.

Whether you create, receive or collect this information, you will need to organise it.

Managing digital information properly is a complex issue. Doing it correctly from the start could save you a lot of time and hassle when preparing a publication or writing up your thesis.

Data Tree is a new online course that has been developed by the Institute for Environmental Analytics. It is designed for PhD students and early career researchers with all you need to know for research data management, along with ways to engage and share data with business, policymakers, media and the wider public.

In this interactive workshop, course Director Vicky Lucas will introduce Data Tree. This will be an opportunity to find out about the leading experts who have contributed to the course, its interactive quizzes, videos and real-world examples, and to delve into some of the topics covered. Attendees of the hour-long session will leave fully prepared to use this excellent free resource to build on their data management skills, solve data handling problems and communicate the results of the research to non-academic audiences.

Read more information about Data Tree

FAIR data are those that are Findable, Accessible, Interoperable and Reusable. Sounds simple enough, but what do each of these terms mean in a practical sense and how can you tell if your own research data is FAIR?

The Research Data Team at the Office of Scholarly Communication join forces with FOSTER Open Science to offer a practical workshop to help you get to grips with the key principles and consider how you can start to make your own data FAIRer.

Once you have completed How FAIR is your research data? An online course (for researchers and postgraduate students in all disciplines) we invite you to attend this workshop session with the Research Data Team from the Office of Scholarly Communication to discuss your experiences in assessing the FAIRness of your data, including any problems you encountered. You are welcome to bring examples of your data to this session to further develop your skills, or try your hand at FAIRifying more example datasets from Apollo.

FAIR data are those that are Findable, Accessible, Interoperable and Reusable. Sounds simple enough, but what do each of these terms mean in a practical sense and how can you tell if your own research data is FAIR?

The Research Data Team at the Office of Scholarly Communication join forces with FOSTER Open Science to offer this practical course to help you get to grips with the key principles and consider how you can start to make your own data FAIRer.

Course commences Monday 4 March: book your place by Thursday 28 February.

This three-week, self-paced course will:

• introduce you to the key terms and explain what they mean in a practical sense
• demonstrate how data management planning can help to make data FAIR from the very start of research projects
• show you how you can use freely available tools to help assess the FAIRness of data
• provide you with the chance to FAIRify your own data, or a sample dataset from the Apollo repository, and get feedback from your peers on its potential reusabilty.

The course consists of an online module followed by two short exercises (see below for details). During this time, participants will need to allocate between 2-4 hours to complete all of the course tasks. Upon successful completion of the course, participants will be awarded with a 'FAIR Data Assessor' badge.

You are then invited to attend a workshop on Monday 25 March with FOSTER and the Research Data Team from the Office of Scholarly Communication to discuss your experiences in assessing the FAIRness of your data, including any problems you encountered. You are welcome to bring examples of your data to this session to further develop your skills, or try your hand at FAIRifying more example datasets from Apollo. Find further details here about How FAIR is your research data?: a workshop (for researchers and postgraduate students in all disciplines).

The course is open to researchers and postgraduate students in all disciplines - arts, humanities and social sciences as well as sciences, technology, engineering, mathematics and medicine.

Advertised on behalf of ReproducibiliTea, the Open Science Journal Club in the Department of Psychology

The Open Science Journal Club invites anyone interested in Open Research to join this lunchtime session, where Dav Clark will introduce Gigantum, a free open source tool designed to streamline reproducible and collaborative data science. Gigantum aims to bring together complex tools, workflows and community approaches that enable exciting research collaborations and also enable others to evaluate and build on your work.

The session will introduce the Gigantum Client, an MIT licensed web application that runs locally, simplifying and automating tools like Docker, Git, and launching environments like JupyterLab. Dav will also describe paid services hosted by Gigantum that enable single-click publication and collaboration from the Client. You will learn about versioning and collaboration features, how to easily move work between local resources and the cloud, as well as new approaches to creating and managing scientific datasets. There will also be the chance to go under the hood to show how sophisticated users (e.g., Research Software Engineers, Data Librarians, etc.) can create customized data science environments that are easy to distribute, and are accessible to users with diverse skill sets.

All welcome - if you aren't a member of the Department of Psychology, please meet at the Department Reception by 12.55 and Ben Farrar will show you to the Nick Macintosh Seminar Room (a second escort will check at 1pm for latecomers!).

This session will include a hands-on demo, so please bring your laptops. You may bring your lunch if you wish, and Dav is happy to join participants for lunch afterwards.