Mini-workshops and demos sessions gave an in depth look at a particular tool or approach and a chance to query developers and experts about how this might apply to attendees areas of work.
Here are the list of mini-workshops and demos that took place at CW17. Due to the demand for slots (and all the cool technology and advice on offer) we had three sessions each of 35 minutes in length.
Each session ran in parallel at different rooms. Each session had 35 minutes for presentation and discussion. Attendees were encouraged to ask questions and enquire about how they could use the approach, tools etc - these sessions had a focus on being interactive.
Session 1
On Tuesday 27 March 2016, 17:15 - 17:50.
Getting your head around IP Law & what's a legal clinic
Speaker: Clemence Tanzi.
Where: YBLT.
In this session we will cover, what a law clinic is and who can receive free legal advice, relevant IPRs for developers to know about, how to use existing content, what infringement is and how to licence IPRs. We will also touch upon the vesting of IPRs in a company.
Software assessment framework
Speaker: Neil Chue Hong.
Where: 1.32.
We will demonstrate a tool and framework to enable you to assess your research software. Our aim is to enable you to identify areas of improvement in your code and see how it compares to other similar software. Come along to find out more, suggest metrics, and learn how you can contribute.
The Brain Imaging Data Structure - a simple way to share data
Speaker: Cyril Pernet.
Where: 1.33.
Neuroimaging experiments result in complicated data that can be arranged in many different ways. So far there is no consensus how to organize and share data obtained in neuroimaging experiments. Even two researchers working in the same lab can opt to arrange their data in a different way. Lack of consensus (or a standard) leads to misunderstandings and time wasted on rearranging data or rewriting scripts expecting certain structure. Here we describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. By using this standard we (i) increase data re-use within and between labs, (ii) facilitate import/export in Databases, (iii) allows data processing automation for large scale meta-analyses. More info at http://bids.neuroimaging.io/.
Session 2
Tuesday 28 March 2016, 14:40 - 15:15.
The EPSRC IoT Research Hub (Petras)
Speaker: David De Roure.
Where: YBLT.
The PETRAS Internet of Things Research Hub is a consortium of nine leading UK universities working together with user partners to explore critical issues in privacy, ethics, trust, reliability, acceptability, and security. Funding for the Hub includes a £9.8 million grant from the Engineering and Physical Sciences Research Council (EPSRC). Over 20 projects address application areas in ambient environments, design and behaviour, health and care, identification, infrastructure, supply and control systems, and transport and mobility. David De Roure is responsible for the Cyber Risk Assessment for Coupled Systems project, and also the harnessing economic value theme.
Software citation
Speaker: Daniel S. Katz.
Where: 1.32.
We now have a set of software citation principles (see 10.7717/peerj-cs.86), and need to move towards implementing them. This session will talk about the principles (10 min) and ask how they could be implemented by the authors and the organizations the audience members represent, and what problems they see with the principles in their various roles.
pyDataView - a framework for data analysis
Speaker: Edward Smith.
Where: 1.33.
In this session, I will present software developed by myself and co-workers over many years for analysing very large 3D vector fields. The software, pyDataView, is open-source and combines an object oriented reader to get data into Python, objects to manipulate and prepare the data, a minimal GUI with sliders for quick insight into that data and tools to help the generation of minimal python scripts for more detailed analysis. The focus is on a limited lightweight interface to provide the user with a quick insight into their data; delegating all complex operations to Python.pyDataView was initially designed to read binary format data (for efficiency) but has since been extended to read a much wider range of formats including LAMMPS and OpenFOAM outputs as well as HDF5 for CFD codes like channelflow.I will outline the design decisions taken in developing this software (after many initial mistakes), outline the Python packages used to analyse and plot the data and discuss the process of making the software sustainable.Please see https://github.com/edwardsmith999/pyDataView for more information on the software.
Session 3
Tuesday 28 March 2016, 15:15 - 15:50.
Getting started with SparkFun
Speaker: Kenji Takeda.
Where: YBLT.
Beyond supplementary material: sharing data effectively through repositories and data journals
Speaker: Andrew Hufton.
Where: 1.32.
The Nature Research journals understand that effective data sharing supports reproducibility and can increase the impact of published works. Indeed, our policies have long recognized that data sharing is a fundamental part of research publication. The increasing complexity and size of research datasets, however, poses challenges for scientists who wish to share their data in a reusable and transparent manner. Based on my experience at Scientific Data, an open-access data-focused journal from Nature Research, I will provide tips on how researchers can share their data in an effective manner that promotes reuse, supports the credibility of their research, and ensures they get proper credit. This will include advice on writing better data-rich papers, the basics of presenting datasets in a useful manner, and tips on how to find the right repository for your data. I will also explain Scientific Data's editorial policies and share some of our experiences peer-reviewing and publishing data so far.
Learn how to create a lesson using Carpentries lesson template
Speaker: Jonah Duckles.
Where: 1.33.
In this hands on mini-workshop, we'll go through the steps necessary to create your own lesson repository on GitHub. After attending this workshop you'll understand how to write lessons in Markdown that are formatted like Software Carpentry lessons.