A Ph.D. student in the life sciences who works on Bioinformatics problems. He has a background in computer science, and data analysis. He is also interested in data visualisation.
A developer with skills around .Net and SQL databases. Also dabbles in chef, nodejs, mongodb, and a few other technologies.
A user experience designer/researcher who should be at home writing up her Masters. Manages the LinkedIn group 'Designing for Health in Australia'... come and talk about making healthcare better through design!
Frontend and backend (Java) developer who should be sleeping now! Getting used to playing with data visualization ... hackathons are great for that! Founder at www.researchyo.com.
Logistics Analyst at Australia Post. Specialises in Data Visualisation, Maps/GIS, and general Analytics.
Data science and analytics consultant - specialist in driving optimal solutions in organisational and marketing strategy through intelligent and creative data mining, statistical analysis and customer insight.
I.T for resilient communities researcher. Maps, society, environment and participatory technology. about.me/fred.michna
Biomedical researcher developing therapies and biomarkers for neurodegenerative disease. Advocate for science and research, and also the research workforce: examining issues including funding, career structure, peer review, gender equity - all fall into science policy and/or policy for science. Molecular biologist, author, educator and mentor.
Each year investigators patiently await the announcements of NHMRC funding. After submitting an application in March and rebutting the reviewers’ comments mid-year, it will not be until October that they find out if they have received funds or not. Keep in mind that academic research is largely funded through grants such as these. There is a lot of publicly available data on investigators and teams awarded NHMRC funding, along with a lot of statistics available. It would be terrific to be able to quickly visualise these results without poring through a large number of pdf files and spreadsheets. If we could quickly generate some user-friendly, easy-to-read graphics that clearly explain where the funding goes each year, it would allow individuals, institutes and other interested parties to readily view the funding landscape.
As an individual researcher or an organisation, such a tool would allow you to work out the demographics of successful applicants, at what level and in what research areas, without having to pore through the data. It will also inform policy development at the institute and national level since any group or association will be able to readily access this information. Just enter the terms you wish to define and ‘voila’, a graph with your desired information will appear.
VizMyGrant is an interactive online tool that enables the user to easily visualise the annual National Health & Medical Research Funding allocation and trends based on publicly available data.
VizMyGrant will enable advocates to rapidly explore the characteristics of grants (such as institutions, gender, state) and create compelling visual aids that can be used to highlight areas for policy improvement.
You need a video uploaded for us to present at closing!
We applied design strategies for analysis and synthesis to approach the idea. Our original aim was to develop an online tool that examined the annual National Health and Medical Research Council (NHMRC) funding landscape every year and over time. As we went through the process, we discovered that including temporal analyses was beyond the scope of this weekend.
Data collection was relatively straight-forward while data cleansing was time-consuming and labour-intensive. During our analysis we realised that we needed to devote resources to a functioning back-end and data architecture, this gave us limited scope for refining visual treatment and interactivity. As a consequence we decided to limit the visualisation data to 2014 data sets.
We arrived at a mixed technology solution in order to take advantage of each individual's skill sets. This has meant that the end solution is hosted across different cloud providers and we bring it together through a project dashboard. This means that the maintenance team need a very diverse range of skills, it might make sense to rationalise this in the future.
- Increase intelligence and flexibility on the data import/cleaning so that Maggie (or someone in her role) can update the dataset as NMHRC releases new updates. Given data is only released once a year, the pragmatic option may be to just hire someone for the 1 day a year that it will take to import the new data sets.
- Clean and Import older data sets
- More thorough quality control (maybe)
- Identify new data sources that can extend the categories and fields that we have available to analyse with
- Incorporate time series filters/views into the current set of visualisations (not done because we only had 2014 data)
- Make all visualisations/tools point at the same source of data, at the moment they need to be manually applied to each solution. A central web based api that can be used by all could be one solution.
Copyright and Licencing
VizMyGrant 2014-2015. Excerpts, code and links may be used, provided that full and clear credit is given to the VizMyGrant team (Scott Ritchie, Sean Fleming, Irith Williams, James Walter, Iulian Stefanica, Aaron McAleese, Fred Michna and Marguerite Evans-Galea) and VizMyGrant at https://viz-my-grant.shinyapps.io/view/ with appropriate and specific direction to the original content.
VizMyGrant by https://github.com/HealthHackAu/HealthHack2014/wiki/VizMyGrant is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at https://viz-my-grant.shinyapps.io/view/.