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Bielefeld Center for Data Science

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News

  • Workshop on Data Literacy at the University:Future Festival 2024

    The workshop "Data Discovery: Gemeinsam die Welt der Datenkompetenzen erkunden" at the University:Future Festival 24 offers the opportunity to delve into the world of data literacy and to get to know an innovative evaluation concept for university teaching. The concept was developed in cooperation with various universities as part of the working group on data literacy of the Stifterverband, in which the Bielefeld Center for Data Science and its managing director Dr. Katharina Weiß are also involved. The workshop is aimed at anyone interested in higher education evaluation and data literacy. The methods presented are not only applicable to data literacy, but can also be transferred to other subject areas. In addition, participants will get a compact overview of key areas of expertise in modern data literacy courses, such as data analysis, critical thinking and ethical use of data.

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  • Successful Workshop: Data Storytelling

    The workshop of BiCDaS and AE06 - Psychological Methods and Evaluation “Mit Daten Geschichten erzählen: Data Storytelling als Ansatz um Datenanalyseergebnisse adressat:innengerecht zu kommunizieren” during the Faculty of Psychology and Sport's Reading and Excursion Week was a complete success. Participants were able to learn the basics of data storytelling, such as how to combine data, visualisations and stories to communicate important issues such as the climate crisis or the coronavirus pandemic in an understandable way. A practical element of the programme was the use of Jupyter notebooks in R for various visualisation methods such as word clouds. For the participants, this was a valuable step towards targeted data communication.

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  • New data lab for sustainability and climate change launched

    A new data lab "Bi DataLab Sustainability and Climate Change" has been founded at Bielefeld University at the Bielefeld Centre for Data Science. Data labs represent an agile approach to (internal) research collaboration, characterised by a thematic focus and a clear needs-driven orientation. The newly founded DataLab Sustainability and Climate Change at BiCDaS invites researchers at Bielefeld University working on sustainability, climate change and environmental protection to the Sustainability Networking Workshop on 7 June from 9 am to 2 pm. During the workshop - after a session of short (approx. 5 min) spotlight presentations - groups of researchers with similar research interests will come together with the aim of networking and thus making a more effective joint contribution to sustainability, e.g. by attracting third party funding for research projects. Interested researchers can register at katharina.weiss@uni-bielefeld.de Please include a brief note on the sustainability relevance of your own research and whether you are interested in submitting a Spotlight contribution.

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  • BiCDaS Lecture Series: "Digital Literacy mit ChatGPT: Kompetenzen zum Umgang mit digitalen Texten"

    On 17 June 2024, Prof. Dr. Andreas Witt from the Leibniz Institute for the German Language Mannheim will give a lecture on "Digital Literacy mit ChatGPT: Kompetenzen zum Umgang mit digitalen Texten". The lecture will take place from 12:15 to 13:45 in the Cafe Nordlicht at Bielefeld University on site but also as a hybrid event online via Zoom. The lecture emphasises digital literacy in the humanities, with a focus on research data and the role of ChatGPT in the development of digital literacy. It begins with a conceptual introduction to digital literacy, highlighting the importance of digital texts in science, and covers their representation, analysis and processing, highlighting Python and spaCy as key tools.

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Weitere Meldungen

More on Data Science...

This is a collection of resources (tools, software, literature, etc.) members of BiCDaS have found useful in their daily work. We also included a list of organizations Data Science enthusiasts may find appealing.

This list is by no means comprehensive and will be extended continually.

Some non-profit organizations related to Data Science

EuADS European Association for Data Science was founded only recently and aims to foster cooperation and communication among Data Scientists in Europe

GfKl The German Gesellschaft für Klassifikation (roughly Society for Classification) celebrates its 40th anniversary in 2017. It has about 300 members and aims to promote data classification and signal processing. Recently Data Science Society has been added as a second name.

DHd The German platform Digital Humanities im deutschsprachigen Raum (roughly Digital Humanities in German-speaking countries) claims to represent the interests of Digital Humanities researchers. Founded in 2013 it has about 400 members (as of 2021).

The Jupyter Notebook is a useful tool for data exploration. Code, plot the results, insert formatted text in any sequence and thereby have your code, results and research notes all intermingled at your fingertips. The Jupyter project originated in Python but can be configured for a wide array of languages. It is continually developed as an open source project coordinated at the Berkeley Institute for Data Science (BIDS).

Python is an all purpose programming language which has gained tremendous popularity in the Data Science community in the last few years. It offers high code readability, high expressiveness and a high-level command set. Its "batteries included" philosophy together with large eco-system of open-source libraries has added substantially to its popularity and utility.

Some modules (libraries) of particular use for data scientist are: numpy, scipy, scikit-learn, pandas and scikit-image.

  • Numpy
  • Scipy
  • SciKit Learn
  • Pandas
  • SciKit Image

The Apache Flink plugin is used for data processing. While it can process finite data sets (batch-mode), it really shines in the processing of continuous data streams. Its integration in the Apache (Web-)Server Software offers some advantages such as cluster-mode (many hosts involved in processing) and fault tolerance.

Data Wrangling with Python

© O'Reilly Media, Inc.

by Jacqueline Kazil, Katharine Jarmul

An excellent introduction to Data Science in Python that is accessible for Python newbies while not being an actual Python textbook. The authors focus just as much on methods of data acquisition, selection, preparation and storytelling, as on the language and different modules (libraries). The authors use real-world data for their examples from public data bases, e.g., the WHO data repository, which makes learning a lot more fun and thrilling. The authors made data and code accessible via git.

ISBN-13: 978-1491948811

Data Science from Scratch

© O'Reilly Media, Inc.

by Joel Gruz

For those already familiar with Python and those preferring a more method-centred approach, this book might be the best alternative. The author covers typical topics for data science beginners like correlation, regression and machine learning and their implementation in Python. He continuously uses the example of the fictive company datascientesta which gives this book a nice red thread.

ISBN-13: 978-1491901427

Not So Standard Deviations

Roger Peng (Johns Hopkins Bloomberg School of Public Health), Hilary Parker (Stitch Fix) and occasional guests talk about Data Science mixed with some real-live-talk and the never-ceasing Python vs. R discussion. This (blog/website/podcast) is entertainment and education at its finest.

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