Science, Data Analytics, Data Science

Software Heritage: Preserving our Software Commons

The Software Commons is the vast body of human knowledge embedded in software source code, that is publicly available and can be freely altered and reused. Free and Open Source Software (FOSS) constitutes the bulk of it. Sadly we seem to be at increasing risk of losing this precious heritage built by the FOSS community over the paste decades: code hosting sites shut down when their popularity decreases, tapes of ancient versions of our toolchain (bit-)rot in basements, etc.

Experience level: 
Intermediate

The Big Data Puzzle - Where Does the Eclipse Piece Fit?

We will introduce a Big Data configuration that uses Avro & Parquet for data formats, Hadoop for storage, and Spark / Hive for running queries. All of these projects are from the Apache Software Foundation and are widely used in the Data Science field. We will show how Eclipse provides an excellent foundation for IDE support and tooling to make it easier to develop solutions based on this technology stack.

Experience level: 
Beginner

Science @ Eclipse

This ignite talk gives an overview of the activities and projects of the Eclipse Science Working Group. The Science Working Group is now about three years old and this talk gives a summary of the global group's efforts to advance software for science.

Experience level: 
Beginner

Simulating Future Mobility

SUMO (Simulation of Urban Mobility) is a microscopic traffic simulator. It has been developed by the German Aerospace Center since 2003 and published as Open Source (see http://sumo.dlr.de). In this talk, SUMO and its capabilities for the realistic simulation of cars, busses, bikes, pedestrians, trains and even ships in cities, such as Berlin, are presented in an overview. A short and hands-on tutorial for the live creation of a simulation scenario is provided.

Experience level: 
Beginner

Charts to the Eclipse people - The making-of

What is better comprehensible: a table with tons of values or a chart? The answer depends on the point of view. The computer better "understands" the table. But we humans are very good when it comes to image recognition. Personally, I prefer the image too. Next question: Is a lightweight charting library available in the Eclipse ecosystem?

Experience level: 
Intermediate

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