Want to share your screen? See the person you're talking to? Contact us via digital library desk! We will be with you shortly.
On the occasion of international Love Data Week from 12.-16.02.24, Lib4RI is organising a series of Coffee Lectures. The topics cover the entire life cycle of research data - from initial management planning, to analysis and visualisation, to application and sharing.
Love Data Week is an international week of action to raise awareness for research data handling. Research institutes from all over the world contribute to this event. Many Swiss institutions participate as well under the umbrella of the Love Data Week Switzerland. See the full programme of events in Switzerland here.
The Coffee Lectures take place Monday through Friday, from 13:00 - 13:15, online via Zoom and they are open to everyone interested. See below for information about the talks, as well as the Zoom links.
Abstract: The talk will introduce open science and data management strategies that enable transparency, research integrity, and knowledge transfer within the context of the Circular Economy and the ReMade@ARI project. It will detail the development and implementation of a comprehensive Data Management Plan aligned with FAIR principles, as well as strategies for open access publishing. The talk will also expand on how research infrastructures integrate local data policies with open science principles.
Abstract: There is a common misconception that High Performance Computing is only for “big data”, huge datasets that require hundreds or thousands of CPUs, and using HPC is too complicated for “normal’ data.
In this coffee lecture I will dispel this notion and show that HPC could be useful for your data-loving needs, and might even help you to time-travel.
Abstract: Poor data charts are hindering the effective transfer of knowledge in academia. On the contrary – clear charts can help your research papers get noticed and your presentations - understood. Martins Zaumanis will show his 8-step method for creating self-explanatory data visualizations. Download a cheat sheet summarizing the 8 steps here.
Abstract: In any HorizonEurope projects Data Management Plans (DMPs) and FAIR Data treatment are now mandatory. Hence each project partner has to contribute, update the DMP on a regular basis, and implement essential parts of FAIR data treatment. We explain, what has to be done, so that you can budget the work accordingly - otherwise you will have to it for free.
Abstract: The data life cycle for FAIR (Findable, Accessible, Interoperable and Reusable) environmental data timeseries is complex. For example, before such timeseries can be made accessible in EnviDat (www.envidat.ch) as FAIR data, they need to be properly understood (in terms of which parameters and which units), be quality controlled, converted into file formats suitable for sharing and reused and enriched with metadata that accurately provide all the necessary information. In this context, the use of MeteoIO (an open-source meteorological data processing library) and NEAD (the non-binary environmental archive data format) can add value to the data by standardisation, metadata enrichment, quality control and potential corrections in a fully reproducible and documented way. This is the main idea behind the Data Life Cycle Integrated System for Sensor Data at WSL/SLF project (DLCIS).