Category Archives: Data management and planning

It’s my data, and I’ll share if I want to

By Tegan Darnell

As a Higher Degree by Research student at USQ, by default, you own the I.P. for your research data. Here are some ideas for maximising your research impact by sharing your data openly with a Creative Commons license.

What is research data?

Research data is described by the Australia National Data Service (ANDS) as

The data, records, files or other evidence, irrespective of their content or form (for example, in print, digital, physical or other forms), that comprise research observations, findings or outcomes, including primary materials and analysed data.

In order to share your data, you will need to have thought of lots of things in advance – before you collect your data (or, with human or animal data, before you apply for ethics approval). You will need to be super organised and create a data management plan.

What is data management?

Data management includes all activities associated with data other than the direct use of the data. It may include:

  • data organisation
  • backups
  • archiving data for long-term preservation
  • data sharing or publishing
  • ensuring security of confidential data and
  • data synchronisation

It is important because good data management practices aligns with your responsibilities under the Australian Code for the Responsible Conduct of Research.

Planning

Give me six hours to chop down a tree and I will spend the first hour sharpening the axe. – Abraham Lincoln

Develop a Data Management Plan. This is a document that contains details of how you will deal with the data you will be gathering. The process will help you to:

  • Make explicit who owns the copyright and intellectual property of the research
  • Secure the protection of research data by making a plan of when, where, how and who will back up the data
  • Organise data by establishing a version control and/or naming convention system
  • Aid data sharing and gaining data citations – increasing your research impact!
  • Ensure long term access to research data – check out the Australian Code for the Responsible Conduct of Research for required retention periods
  • Gain access to existing research data sets to reduce your workload

If you are applying for a grant, you may be required to complete a Data Management Plan as part of your grant application.

The Human Research Ethics Application form will ask questions about how you are going to handle your research data, so before you complete your ethics application, it is an ideal time to do a data management plan.

To assist you to develop data management strategies, USQ has a Data Management Plan template you can use.

Publishing

Data can be published via:

  • sharing information about research datasets through metadata records in repositories, most often at institutions (eg. this record in the CSIRO Data Access Portal)
  • metadata records put into Research Data Australia or listed in discipline-specific repositories
  • online repository services such as Figshare
  • through Data journals
  • informal publication such as via personal or commercial repositories or websites

Most research data is stored and/or described in a research data repository.  We have data described in our USQ ePrints repository.

What to consider:

(information provided by ANDS)

Check out this awesome example of open data from Flinders University, the Australasian Heritage Software database. Kooky!

If you are interested in publishing your data, contact researchlibrarian@usq.edu.au, where a librarian will be able to guide you through the process and refer you to any services and resources you might need.

USQ’s Inaugural Software Carpentry Session

By Francis Gacenga

This week 29 USQ researchers staff and students from across USQ’s research institutes, centres and faculties participated in the first ever Software Carpentry Workshop in Toowoomba.

Image courtesy of USQ Photography

USQs Inaugural Software Carpentry class

Software Carpentry workshops aim to help researchers “get more done in less time and with less pain by teaching them basic lab skills for research computing”1. The hands-on workshop at USQ’s Toowoomba campus covered basic research computing concepts focusing on task automation, data management, program design, and version control. A common challenge faced by most researchers is getting the most done within time and funding constraints. IT systems are designed to help but sometimes create complications and get in the way. The researchers who attended the Software Carpentry Workshop were introduced to ways of getting the most of IT services and systems to efficiently complete common research tasks.

The researchers first learnt how to automate common tasks such as directory, folder and file management, using pipelines of commands and how to build efficient and automated workflows using the Unix shell, a computer operating system commonly used in Virtual Machines (VMs) and High Performance Computers (HPC). A basic introduction to programming with Python was provided and participants familiarised with using Python for data analysis and presentation. The participants got an introduction to automated version control using Git and learnt how to use Git to track changes, version and merge files while keeping repositories in sync across different computers facilitating collaboration among different people. The workshop provides an essential foundation in getting the most out of research computing and data services and infrastructure provided at no cost to researchers at USQ by the National eResearch Collaboration Tools and Resources (NeCTAR)2, National Computational Infrastructure (NCI)3 and Research Data Services (RDS)4 through the QCIF (Queensland Cyber Infrastructure Foundation)5.

The event has received positive feedback and there are an additional 15 who have expressed interest in attending a second session to cover statistical analysis. The workshop provided a gentle introduction to working with a computer command line interface, opening up new possibilities and resources that enhance researchers outcomes and experiences. The format of Software Carpentry Workshops make it easy for all to learn as no background training is required. At the workshop there were three instructors and seven helpers in the room ensuring that help was always available when required.

The lessons covered are available online for the participants and anyone interested to access freely online at http://software-carpentry.org/lessons/. There is also a vibrant and very helpful software carpentry community online that is ready to provide ongoing help as well as ongoing local support from QCIF’s eResearch Analysts.

The workshop was organised by the Office of Research Development, sponsored by the ReDTrain initiative, supported by QCIF and the Software Carpentry Foundation and administered by certified instructors and volunteers from UQ and USQ. Researchers had opportunities to learn as well as network over the two days. The workshop was a success and there are plans to run more Software Carpentry Workshops in the future. If you would like to learn more about Software Carpentry or are interested in attending a workshop contact the author of the blog at eResearchServices@usq.edu.au.

 

Reference:

  1. http://software-carpentry.org/workshops/
  2. https://nectar.org.au
  3. https://www.rds.edu.au
  4. http://nci.org.au
  5. https://www.qcif.edu.au

eResearch and Librarians

By Robyn Edmanson

As a librarian I’m interested in the future skills we need to support researchers. In the past decade, eResearch practices and processes have evolved along with library support services.

eResearch is:

‘research activities that use a spectrum of advanced information and communication technologies and that embrace new research methodologies emerging from increasing access to advanced networks, services and tool’

from The Department of Education, Employment and Workplace Relations 2006

Since then, eResearch has grown both locally and internationally alongside the portability and sophistication of ICTs.

So too data collections, sample sizes and data management practices have evolved and improved as researchers, and librarians supporting their work, have come to grips with new skill-sets surrounding five key areas:

  1. Collaborative technologies: IM, Sharepoint, Google Tools, Social Bookmarking, new video conferencing technologies such as zoom
  2. Research data management: experimental, observational and/ computational data; data storage and curation; derived data and more
  3. Scholarly communication: Endnote, Zotero, Refworks, Mendeley; Creative Commons licensing; electronic publishing – both Open Access and subscriber; bibliometrics & altmetrics; institutional repositories; author identifiers, e.g. ORCID ID, Researcher ID.
  4. Visualisation: Learning Analytics and dashboards
  5. Data collection & analysis: qualitative, quantitative, mixed methods analyses, data mining, programming languages such as R and Python for meaningful information.

While librarians’ skills have evolved with advances in these key areas, data analysis is a new and exciting area of eResearch involving open-source software and a new digital mindset. The automation requirements of a lot of eResearch projects require programming and analysis skills which is where librarians can help with a new Library Carpentry Toolbox supported by the Australian National Data Service (ANDS).

Software training for librarians is an important new tool made possible with open source technology; important new skills to safeguard against data loss, enable data re-use and ensure against copyright mismanagement.

Editors Note: USQ eResearch is running ‘Software Carpentry’ sessions on the 18th -19th July 2016. Find out more about ‘Software Carpentry’ here.

Data Management

By Robyn Edmanson

As an information professional and fledgling researcher, I care about data management.

Why?

Because funding agencies, journals, and other stakeholders increasingly require you and I, the data producers, to share, archive, and plan for the management of our data. We need data management and curation knowledge and skills that support the long-term preservation, access, and reuse of data.

Effectively managing data also helps to optimise research output; increase research impact; and support open scientific inquiry.

I’m doing the Australian National Data Service’s 23 (research data) Things training to help me manage our research data throughout the entire data lifecycle from project planning to the end of the project when data ideally are shared and made available. Not simply stored on the mercurial USB, but in a trustworthy repository such as QRISCloud which is QCIF’s (Queensland Cyber Infrastructure Foundations) trusted online repository.