Publication

Research Data Lunch Talk - 14th meeting - How to manage big datasets: from arts to stars

2024

Abstract

The 14th event of the Research Data Lunch Talks entitled “How to manage big datasets: from art to stars”, took place on November 21st, 2024. Open to everyone interested, to connect with experts from the EPFL community, and discover how researchers across fields tackle the management of big datasets.

Short talks, followed by a panel for Q&A, from: “From Manuscripts to Petabytes: The Scale of Cultural Data in the Digital Age” by Dr. Kirell Benzi, Scientist in Visual Intelligence and Transportation (PDF not available) “Community Pulse: Navigating the Vastness of Data–Lessons from the ORD Hackathon” by Dr. Oksana Riba Grognuz, Head of ORD Engagement & Services Team at the Swiss Data Science Center “Efficient Web Visualization of Geospatial and Timeseries Datasets” by Pierre Ripoll, Data Engineer and Full-Stack Developer at ENAC-IT4R “Navigating the Cosmic Data: Insights from Modern Astrophysics” by Dr. Volodymyr Savchenko, Data Scientist of EPFL Laboratory of Astrophysics

Finally, the EPFL RDM Team presented an overview of Research Data Management initiatives at EPFL and beyond.

Official source

https://infoscience.epfl.ch/entities/publication/36f14ad6-3b30-4c6a-9118-2346d8f8a83e

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2024

Abstract

Finally, the EPFL RDM Team presented an overview of Research Data Management initiatives at EPFL and beyond.

Official source

https://infoscience.epfl.ch/entities/publication/36f14ad6-3b30-4c6a-9118-2346d8f8a83e

About this result

Related concepts (32)

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Related publications (27)

Research Data Lunch Talk - 14th meeting - How to manage big datasets: from arts to stars

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Using recommender systems to analyze and predict plant communities from partial assemblages

Data for: Medina et al., Inactivation of surrogate respiratory bacteria is driven by osmotic pressure change in drying saliva microdroplets

Retrieval of the hail size number distribution from polarimetric radar data using the double-moment normalization