Debra Bordignon, chief technology officer, Dimension Data Australia, said in the partnership with Western Sydney University, it has created an ecosystem approach that enables mass data collection, aggregation and analysis from a wide variety of sources including personal data, the Internet of Things, social channels as well as existing data sets and applications.
“No matter where the data originates, it can integrate with mass data observations,” Bordignon says.
According to Dimension Data, mass data observations — developed under a co-innovation agreement between it and WSU — makes it easier and more cost-effective for researchers to combine and analyse a multiverse of data sources, including public datasets, archives, social data feeds, data from IoT devices, and qualitative and quantitative data contributed by communities of data contributors.
“Discrete and disparate data sets can now be combined securely and ethically in new and exciting ways which will reassure data owners, and revolutionise the way organisations engage with communities and how data can be shared to conduct qualitative and quantitative research,” she says.
Professor Deborah Sweeney, deputy vice-chancellor, research and innovation, WSU, added, “We were first exposed to the power of San-Shi after touring the NTT R&D facility in Japan last year. We identified it as a complementary solution to Mass Data Observations, as the platform demands a computing environment that enables aggregation and processing of personal information while keeping the data securely protected at all times,”
Professor Sweeney says the need to ensure that the data collected is held securely by the university is paramount to the viability of Mass Data Observations.
“If we cannot guarantee that the data is secure and meets all of our regulatory and ethical requirements, then we cannot ask students and future participants to get on board, and future research opportunities would be held back.”
Both Dimension Data and WSU say trials of mass data observations to date have surpassed expectations, with more than 2500 WSU student volunteers providing over 20,000 individual responses to surveys and polls through the app.
And they say that, with users’ full agreement, researchers can bring together these responses and first-hand experiences and combine them with other data sets such as census data, to explore correlations and deep insights.
The next stage involves early adopter trials with interested organisations and is expected to cover health and community-related use cases, with a managed service offering expected to follow.