I usually don’t usually ask for much, but I’d really appreciate if you all could spend some time in the gallery and let me know what you think in the comments below or directly via email. It’s still a work in progress, but hoping that this gallery is a meaningful companion for the newsletter and can also live as a standalone way for folks to interact with with data analytics and visualizations. There is also functionality built into the individual story pages for you to provide thoughts/feedback. However, as an enterprise trend, these lightweight, strategic Web apps that combine.
'Mashup' has emerged as the buzzword of the Web 2.0 world. You can browse through collections of visualizations as well as dig deeper into the stories behind specific collections. The platform is also billed as a tool for constructing new business applications that integrate Web and enterprise data with business processes, which is Denodos definition of an enterprise data mashup.
The website’s organization is primarily inspired by physical art galleries. So I’ve put together a website that’s designed to be a place where audiences can interact with the data and stories in a more intersectional way. Given that that the content is designed to be intersectional, I realize that it can often be a challenge to piece together intersections between older/newer segments in the way that the newsletter is currently organized. The paper proposes an approach called Mashroom+ to support human-machine interactive data mashup, which can better handle uncertainties during the semantic matching process.
I really enjoy the newsletter medium and will continue to be sending out things to those who subscribe to the Data Mashup on a weekly/biweekly basis. To integrate data on the Internet, we often have to deal with uncertainties when matching data schemas from different sources. (Please note the Met Office’s data licence, which is.
#Data mashup how to#
For the last few months, I’ve been noodling around with how to better organize content. MEDMI contains a number of different environmental and health datasets, including the Met Office’s MIDAS, NCIC, AURN and stratospheric ozone databases, as well as data on infectious diseases from Public Health England’s Second Generation Surveillance System (SGSS) database.
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