The Eclipse January project provides standardized numerical arrays in Java that are similar to the popular numpy library. This library is used extensively at Diamond Light Source for managing the data, lazy loading, python integration, and plotting as part of DAWNSci. Eclipse January is also used for IoT applications such as edge processing.
Science, Data Analytics, Data Science
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.
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.
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.
Have you ever dreamt of customizing your Eclipse workbench using your favorite scripting language? Do you want to add new functions to your favorite IDE without having to learn how to develop an Eclipse plugin? Do you want to provide the ultimate flexibility to your users to let them prototype their own Eclipse plugins?
We run data acquisition at the UK's biggest science project using Java. This year we completed a migration of around three million lines of code in our Java servers to OSGi running with Equinox and declarative services. This is the story of how we did it, the pitfalls and real world examples of what happened.
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.
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?