17. června 2020 11:37
Invitation to the Webinar on Metadata & Data Sharing and Management Principles
We would like to cordially invite you to the upcoming webinar
dedicated to metadata and FAIR sharing principles for best practice in
research data management that is scheduled on Tuesday 23rd June at 10 AM CEST.
During the webinar you will learn:
Metadata Introduction The
importance of metadata is often underestimated. For data users are
metadata commonly regarded as a necessary evil, and something mandatory
to the data creating and dataset publishing process. This presentation
offers a different point of view: metadata are a red line connecting the
geographical tools and applications. No matter when searching for
relevant data, Web services, explaining underlying models, displaying
predicted situation in a map etc. This presentation will guide you a way
to revoke an artificial border between data and metadata.
Predicting cloudness of satellite images through (meta)data Metadata
does not have to be texts! Metadata in a textual way have in some cases
a low information value for a user; e.g. a satellite image is covered
from 60% by clouds. Will my farm be covered with clouds or not? This
presentation will guide you through another (meta)data use case:
metadata as geometry/graphics. Moreover, the presentation deals with
cloudiness predictions as well as notification mechanisms through e-mail
and SMS.
Micka MIcKa http://micka.bnhelp.cz/
is a complex solution for metadata management and for Spatial Data
Infrastructure (SDI) and geoportal building. It contains tools for
editing and management of metadata for spatial information, web services
and other sources (documents, web sites, etc.). It includes their
search on the Internet, portrayal in map or download to local computer.
OpenMicka is freely available while Micka is a commercial tool. The
designation (Open)Micka is used hereinafter for features similar to both
licensing versions. Commercial version of Micka is also available free
of charge for the duration of the SIEUSOIL project. The full
documentation to both versions is stored at https://github.com/hsrs-cz/Micka . MicKa is now part of SmartAfriHub https://www.smartafrihub.com/cs/metadata
FAIR data principles for best practice in research data management The
FAIR data principles identify four important characteristics of
datasets (Findable, Accessible, Interoperable and Reusable) that will
make them easier to use. These principles have been developed to help
publishers assess whether individual datasets are published in a FAIR
and open way. They have been adopted by the research community, where
they capture a set of best practices that apply when publishing any type
of dataset. FAIR data principles can be applied to data that exists at
any point on the data spectrum. The principles emphasise clear licensing
and recommend standard licences ‒ like those of creative commons ‒ but
do not suggest data should be either closed, shared or open. For
instance, sensitive personal data only available to researchers under
limited data sharing agreements can still benefit from being FAIR to
ensure researchers can easily find, access and reuse that data.
You will hear from:
The webinar is open to everyone – students,
researchers, data analytics, NGO, African and European projects, anybody
in Africa and beyond, who is dealing with data management.