information analyst

"Scientific Data to complement and promote public data repositories

Scientific Data will be a forum for publications about datasets, but will not be a repository for primary datasets. Primary data associated with Data Descriptors will be stored in one or more external data repositories. Why this distinction?

 This strategy helps us draw some clear lines around the goals of Scientific Data. By ensuring that the primary datasets are stored in external systems, we make it crystal clear that our goal is to help authors publish content that promotes the scientific value and reusability of their datasets, not to control access to data. We feel that this is a progressive strategy that will help promote collaboration and data consolidation, rather than fragmentation"

from source: http://blogs.nature.com/

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Andy Hobsbawm's (one of the founders of the business EVRYTHNG) business gives me a headache quite quickly as I struggle to imagine the implications of the humungous data generated by everything we touch. And then there's the data generated by mixing up the data with other data in order to create more data that predicts the future and reshapes our existence. Got that? Just a little scary, yes?

I don't mind my bike or my fridge talking about my habits but the implications of underwear or individual deodorants having their own Facebook page, or the web-of-things equivalent, is mind-boggling. What if - oh dear, how embarrassing - you don't appear to have a deodorant life? Too much information or not enough, either way as we become even more defined by our consumption this could get vicious. I can sense a lobby forming to say our rights are being eroded in ways that go way beyond what Google's done to us so far.

"Une analyse complète sou forme d'infographie de votre présence et de votre activité sur le réseau social Facebook. Un résultat impressionant fourni par le moteur Wolfram."

The Google Public Data Explorer makes large datasets easy to explore, visualize and communicate. As the charts and maps animate over time, the changes in the world become easier to understand.

Graphics, charts, diagrams and visual data representations have been published on books, newspapers and magazines since they've existed, not to mention old maps and scientific illustrations...

Despite the lack of tools such as the ones we have at our disposal nowadays, they are as inspiring and important as the best contemporary visualizations. Visit the article link for a gallery of vintage visualizations...

For many data visualization projects, information comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data. For this reason, it's critical to have an in-depth and thorough knowledge and understanding of the information from aggregated information. There are several different visualization techniques that open up once we have the original data, such as Euler diagrams and parallel sets.

The extra information that can be obtained from visualizations is important to gaining a full understanding of the data, and it can lead to a much more interesting story, as well as far better visualizations and more accurate connections and links within those visualizations.

So, when gathering data about something, remember to dig deeper into it, as there are many important connections that happen within data that can provide knowledge beyond just a simple average or total.

To learn more about the value of these connections, sourcing accurate data, and how it is transformed into useful graphics, read the complete article and check out the case study used to convey the main points outlined above...