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TA1 "Data for Science" Vorlesung
18 April 2023
TA1 "Data for Science" Vorlesung https://www.daphne4nfdi.de/downloads/Events/TA1%20lecture%20series_Krahl.pdf https://pan-training.eu/events/ta1-data-for-science-vorlesung-a99bc043-c4f9-4eb9-b068-52fedfd00d74 The FAIR Data Principles require that data is described with rich metadata and that it is associated with detailed provenance. Without the indication of the instrument that has been used to collect the data, this description will be incomplete. In order to make this indication reliable and persistent, we need a persistent identifier for the instrument. The Persistent Identification of Instruments Working Group in the Research Data Alliance has explored a community-driven solution for globally unique identification of measuring instruments operated in the sciences. The group formulated a schema for the metadata to identify the instrument that should be stored along with the identifier in the PID infrastructure and it tested potential implementations with infrastructure providers, namely ePIC Handles and DataCite DOIs. 2023-04-18 14:00:00 UTC 2023-04-18 15:00:00 UTC [] [] research data scientist workshops_and_courses [] FAIR Data Principlesmetadatadata provenancepersistent identifiers -
Fundamentals of Scientific Metadata: Why Context Matters
18 - 19 June 2024
Fundamentals of Scientific Metadata: Why Context Matters https://events.hifis.net/event/1520/ https://pan-training.eu/events/fundamentals-of-scientific-metadata-why-context-matters This course is an entry-level introduction to the fundamentals of scientific metadata for PhD students, early-career researchers, and postdocs. In this course we will look at the intricate relationship between (digital) research data, metadata, and knowledge; discuss why metadata is critical in today’s research; and explain some of the technologies and concepts related to structured machine-readable metadata. Have you ever struggled to make sense of scientific data provided by a collaborator? Or, even worse, to understand your own data five months after publication... Do you have difficulties in meeting the data description requirements of your funding agency? Do you want your data to have lasting value; but don’t know how to ensure that? Precise and structured descriptions of research data are key for scientific exchange and progress - and for ensuring recognition of your effort in data collection. The solution: make your data findable, accessible, interoperable, and reusable - by describing them with metadata. This course is targeted especially at scientific staff and researchers in the Helmholtz Research Field Matter but is open to anyone who would like to better understand research data annotation with metadata. *What You Will Learn*: * Understanding the vital differences between data and metadata. * Techniques for annotating research data using structured metadata. * Identifying and implementing appropriate metadata frameworks and data repositories. * Developing basic skills in Markdown, JSON, XML. * Exploring tools to improve your metadata annotation capabilities. * Recognizing the role of structured metadata in enhancing your scientific visibility. In this course, we will specifically focus on matter-related datasets, formats, and metadata schemas. However, it is open to anyone interested in learning about structured metadata and its importance in scientific research. 2024-06-18 09:00:00 UTC 2024-06-19 12:30:00 UTC [] [] [] workshops_and_courses [] metadatadata managementdata repositorymatterdataset -
Lecture series "Experiments and Data at Photon and Neutron Facilities"
12 November 2024
Lecture series "Experiments and Data at Photon and Neutron Facilities" https://events.hifis.net/event/1811/ https://pan-training.eu/events/lecture-series-experiments-and-data-at-photon-and-neutron-facilities This lecture series, organized by the DAPHNE4NFDI consortium, aims at introducing to several common experimental techniques being used at large-scales facilities, i. e. neutron sources and synchrotrons, and various data aspects. The lectures will cover the basics of the methods and show practical application of these. In addition, challenges and opportunities on how to properly and efficiently handle the large datasets produced during experiments (i.e., improved research data management, automatic ingestion of metadata, artificial intelligence and machine learning models) are tackled to emphasize this mostly hidden aspect as well. The lecture series is aimed at MSc and PhD students, but also interested postdocs. The course corresponds to 2 ECTS points. The lecture series consists of 16 lectures and takes place every Tuesday at 3:30 PM (CET), starting from 22/10/2024. Please check content material before each lecture to get the latest version. **Material only for registered users** 2024-11-12 15:30:00 UTC 2024-11-12 17:00:00 UTC DAPHNE4NFDI x-ray absorption spectroscopy Karlsruhe Institute of Technology (KIT) vitaly.biniyaminov@kit.edu Deutsche Forschungsgemeinschaft (DFG) masters studentsPhD studentspostdocs workshops_and_courses [] Data at Photon and Neutron Facilitiesdata scienceXRDmetadatarefXAS
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