September 2017: Cartographic License and Building Maps That Work

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Presented by Sarah Battersby

Senior Research Scientist at Tableau Software

We live in a data rich world and many of the data that we encounter have a geographic link, such as a point coordinate, an address, a state, or country name.  Maps are a key part of understanding geographically linked data and utilizing it in decision making.  In designing maps, virtually anyone with a computer and an internet connection can be a cartographer – regardless of knowledge of principles of spatial data or visual and cartographic communication best practices.  The good news about this democratization of cartography is that everyone is empowered to explore their own data with maps.  The bad news is that anyone can make a map.  While many map authoring tools help guide the design, it is still easy to unintentionally (or occasionally intentionally) mislead readers.  The variant of the truth that we find in maps is largely driven by choices that the cartographer makes in the data collection, cleaning, analysis, and visualization process.  In this presentation I consider issues of how the map designer and reader perceive mapped data and where “noise” can creep into the communication to distort the intended message.

July 2017: Data Science, Predictive Analytics

Presented by Dean Abbott

Chief Data Scientist, SmarterHQ

Most of what data scientists do is nothing new, and much of what’s new is really a throwback to what we used to do 20 years ago. So why data science so popular now? In this talk, Dean will describe what differentiates data science from related fields like Business Intelligence, Predictive Analytics, and Statistics, and will illustrate the use of data science from case studies in customer analytics and fraud detection.

June 2017: How Automation Can Help You Implement Governed Data Discovery

Presented by Joseph Treadwell

Lead Solution Specialist at TimeXtender North America

In today’s age of analytics, businesses are demanding self-service access to their corporate data, while struggling to make sense of raw data at the source. In response to this, recent analyst reports have revealed a new form of BI architecture known as Governed Data Discovery.

May 2017: Semantic Data Mining & Deep Learning in Health Datasets

Presented by Dr. Dejing Dou

Professor, University of Oregon, Computer and Information Science Department

UPDATE: A PDF of Dr. Dejing Dou’s presentation is available for download.

Ontologies have been well used in the biomedical and health domains. Semantic data mining refers to the data mining tasks that systematically incorporate domain knowledge, especially formal semantics, into the process. The use of ontologies in mining healthcare and medicine data is a natural fit. In this talk, we focus on the use of formal (Semantic Web) ontologies in two data mining and deep learning tasks in health datasets.

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