Lecture

Critical Data Studies: Reproducibility and Renku

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

HUM-485: Data in context: Critical Data Studies I

Le cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interdiscip ...

Description

This lecture covers the importance of reproducibility in data science, focusing on the origins of the scientific method and the current crisis of reproducibility in research. It also introduces Renku, a platform for managing data-driven projects. The lecture discusses the technical stack needed for reproducibility, policy implications of open science, and the FAIR principles. Students are guided on how to use Renku for their projects and the tools available for ensuring reproducibility.

Official source

Related concepts (32)

Renku

, or haikai no renga, is a Japanese form of popular collaborative linked verse poetry. It is a development of the older Japanese poetic tradition of ushin renga, or orthodox collaborative linked verse. At renku gatherings participating poets take turns providing alternating verses of 17 and 14 morae. Initially haikai no renga distinguished itself through vulgarity and coarseness of wit, before growing into a legitimate artistic tradition, and eventually giving birth to the haiku form of Japanese poetry.

Hokku

is the opening stanza of a Japanese orthodox collaborative linked poem, renga, or of its later derivative, renku (haikai no renga). From the time of Matsuo Bashō (1644–1694), the hokku began to appear as an independent poem, and was also incorporated in haibun (in combination with prose). In the late 19th century, Masaoka Shiki (1867–1902) renamed the standalone hokku as "haiku", and the latter term is now generally applied retrospectively to all hokku appearing independently of renku or renga, irrespective of when they were written.

Haiku

Haiku is a type of short form poetry that originated in Japan. Traditional Japanese haiku consist of three phrases composed of 17 phonetic units (called on in Japanese, which are similar to syllables) in a 5, 7, 5 pattern; that include a kireji, or "cutting word"; and a kigo, or seasonal reference. Similar poems that do not adhere to these rules are generally classified as senryū. Haiku originated as an opening part of a larger Japanese poem called renga.

Kireji

are a special category of words used in certain types of Japanese traditional poetry. It is regarded as a requirement in traditional haiku, as well as in the hokku, or opening verse, of both classical renga and its derivative renku (haikai no renga). There is no exact equivalent of kireji in English, and its function can be difficult to define. It is said to supply structural support to the verse. When placed at the end of a verse, it provides a dignified ending, concluding the verse with a heightened sense of closure.

Renga

Renga (連歌, linked poem) is a genre of Japanese collaborative poetry in which alternating stanzas, or ku (句), of 5-7-5 and 7-7 mora (sound units, not to be confused with syllables) per line are linked in succession by multiple poets. Known as tsukuba no michi (筑波の道 The Way of Tsukuba) after the famous Tsukuba Mountain in the Kantō region, the form of poetry is said to have originated in a two-verse poetry exchange by Yamato Takeru and later gave birth to the genres haikai (俳諧) and haiku (俳句).

Related lectures (64)

Renku: Collaborative Data Science

Introduces Renku, a platform for collaborative data science enabling reproducibility and promoting code and data reusability.

Elements of Collaborative Data Science

Introduces collaborative data science tools like Jupyter notebooks, Docker, and Git, emphasizing data versioning and containerization.

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Gitlab Agent for Kubernetes (`agentk`)

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

General Introduction to Big Data