Using Web Data to Visualize and Track Disease Outbreak for Global Security

Last week we highlighted a case study about how an insurance group used our BITS dataset to help a chief actuary improve the underwriting process.  We explained how an actuary from an insurance organization is using a dataset of over 9,000 news sources to increase pricing efficiency. Today, we hope to further explain how customers are using our BITS dataset, but this time we’ll explore how a Chief Security Officer is using BITS to help track the outbreak of disease globally.

The Chief Security Officer of a major mining organization approached us hoping to create a better dashboard for his organization’s data.  With human assets scattered in close to 100 different countries, he wanted to more accurately track where disease outbreaks were occurring. It’s important to note that he already had access to some disease outbreak datasets, but felt the vast majority of this data –stemming from national news sources – was oftentimes significantly behind in reporting.

He hoped to find a new dataset and get new dashboards that would better reflect the happenings of disease and where they were occurring. Since our BITS dataset contains a large amount of national and local news reporting on global outbreaks, it was a perfect fit for his organization.

For this specific project, we created an entirely new disease outbreak entity using Rosoka . This new entity captures the relationships between specific locations and disease. An example of that tagging is shown below.TaggingV2

What the data looks like

After we harvested the articles from millions of web pages, we extracted the disease and location entities and were ready to start using the data!

We worked on structuring the data into a format that can be used for analysis. The table below shows the data loaded directly into a visualization tool. Every row within a document refers to a disease and its outbreak location that had been tagged by Rosoka.


Visualizing Data

After the data was harvested and enriched, we then loaded the outbreak data into a visualization tool called Tableau for easier analysis.VisualizationDiseaseTrends