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We conducted a survey to determine if the existing AuScope Virtual Research Environment (AVRE) still met current researcher needs. We present results from the interviews that gauge the level of interest and engagement with various topics and technologies, including Jupyter Notebooks, machine readable APIs, FAIR Data, metadata and federated portals. Our analysis of the results indicates that many researchers would benefit from more flexible and extendable data access and analysis technologies such as machine readable APIs and Python Notebooks, rather than pre-packaged applications. Over the past decade considerable effort has been spent building web-based geospatial portals that provide access to prefabricated analysis-ready data products, built-in tools and fixed workflows. The desire for adding new features to these portals has been eclipsed by a strong demand for easier access to both less processed and analysis-ready datasets via human-centred and machine-friendly interfaces.
Funder: AuScope Ltd
FAIR Data Principles, Machine Readable APIs, Jupyter Notebooks, User Survey
FAIR Data Principles, Machine Readable APIs, Jupyter Notebooks, User Survey
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 3 | |
| downloads | 4 |

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