Amanda Miotto - Amanda Miotto is an eResearch Analyst for Griffith University and QCIF. She started off in the field of Bioinformatics and learnt to appreciate the beauty of science before discovering the joys of coding. She is also heavily involved in Software Carpentry, Hacky Hours and ResBaz, and has developed on platforms around HPC and scientific portals.


Julie Toohey - Julie Toohey is a Library Research Data Management Specialist at Griffith University Library. Julie has an extensive career in academic libraries and is passionate about research data management practices. Previously, Julie co-facilitated the Australian National Data Services 23 Things (research data) Health and Medical Data Community series and is currently a member of the QULOC Research Support Working Party. Julie works closely with Griffith eResearch Services delivering education awareness programs around managing research data, reproducible research and working with sensitive data. Julie has co-authored several research data related publications with Griffith researchers and eResearch Services partners. https://orcid.org/0000-0002-4249-8180

Title: Going down the Reproducible Research pathway: You have to begin somewhere, right?

Abstract: The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important.
Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program

About The Language Technology and Data Analysis Laboratory (LADAL) Webinars 2021

The Language Technology and Data Analysis Laboratory (LADAL) is school-based support infrastructure for computational humanities research established and maintained by the UQ School of Languages and Cultures. The LADAL is part of the ARDC Australian Text Analytics Platform (ATAP) which represents a nation-wide attempt to foster computational skills in HASS. It collaborates with and shares expertise with several Australian and international centres, institutions, researchers, and experts.

The LADAL consists of a specialist computing lab for language-based computational and experimental work (the Computational and Experimental Workshop) and an online virtual lab (the LADAL website). The LADAL website offers self-guided study materials and hands-on tutorials on topics relating to digital tools, computational methods for data extraction and processing, data visualization, statistical analyses of language data, and provides links to further resources and short descriptions of digital tools relevant for digital HASS research. In addition, the LADAL offers face-to-face consultations and specialized workshops. SLC researchers are encouraged to contact LADAL staff for advice and guidance on matters relating to digital research tools, data visualization, various statistical procedures, and text analytics.  As such, the LADAL offers pathways to new research possibilities in HASS with a focus on computational quantitative text analytics.