Virtual BSC RS: "Users of Big Earth Data - An analysis of current and future user requirements of (cloud-based) data systems"

Data: 23/Mar/2021 Time: 15:00

Place:

Virtual seminar via Zoom, with required registration

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Objectives

You can watch the seminar in this link.
 
Abstract:The broad dissemination of open data policies for Big Earth Data leads to a diversification of users.
The literacy in data and data handling differ for each user group, resulting in different needs and requirements.
In addition, the development of cloud-based data systems challenges traditional workflows of all users.
In order to tailor new cloud-based data systems for Earth data users, a better understanding of users in terms of
the type of data they explore, the applications they need the data for, the way they access and process data,
and the challenges they face is required. We run a comprehensive web-based user survey to better understand current
and future user requirements and users’ motivation to migrate their processing tasks to cloud-based data services.
The presentation highlights the results of the user survey with a specific focus on the current data challenges users face and
how users would like to use cloud-based data services in the future.

Short BIO: Julia Wagemann is a geospatial analyst, PhD candidate and community-builder
who promotesthe use of large volumes of open meteorological and climate data.
For the past six years, her work has been in the intersection of data providers and data
users and she strongly advocates for a better understanding of user
requirements and needs in order to unleash the full potential of open data.
This interest is also reflected in her research, where she explores user
requirements, training and interoperability needs of cloud-based services for
Big Earth Data. She regularly engages with the user community and develops and
runs training on open Big Earth Data with Jupyter notebooks and Python.

Speakers

Julia is a geospatial analyst, PhD candidate and community-builder who promotes
the use of large volumes of open meteorological and climate data.