On Open Big Data, our directory of open access datasets for social science research, we have published a master dataset of historical advertisements of The Economist now.
This FAIR dataset contains metadata of 512.599 historical advertisements from all 8,840 issues of The Economist magazine, years 1843 to 2014. It is part of a series of datasets related to The Economist Historical Archive.
Check this out if you are looking for historical data on advertisements for your research: http://openbigdata.directory/
During the Berlin Science Week 2021, NFDI – Nationale Forschungsdateninfrastruktur e.V. will organize the virtual NFDI Science Slam on 9 November 2021 at 17:00 – 19:00 h CEST. If you want to learn more about NFDI and the various NFDI consortia, secure your seat now!
Berlin Science Week provides international scientists and science driven organizations with a stage to share insights into current topics, discuss grand challenges and envision the future together. Throughout ten festival days and beyond, Berlin Science Week fosters debates and knowledge exchange in an open and interdisciplinary spirit.
The conference takes place from 1 to 10 November 2021. The full conference program is available on the conference website.
We are looking forward to present BERD together with BioDATEN, MoMaF, SDC4Lit and bw2FDM at the 7th bwHPC Symposium on November 8, 2021. The conference focuses on the presentation of scientific projects and success stories carried out with the help of bwHPC high performance computing as well as the BaWü data federation. The event offers a unique opportunity to engage in an active dialogue between the scientists, operators of the bwHPC services, and members of the bwHPC-S5 support centers.
Details regarding program and registration are available here.
Our colleagues Irene Schumm, Markus Herklotz and Lars Oberländer presented as part of this years’ Data Literacy Essentials series on data literacy, data collection as well as data protection and copyright in research data.
The Data Literacy Essentials are 45-minute (online) seminars designed to familiarize students with the basics of working with data early in their studies. The series explicitly addresses students whose degree programs do not focus on these topics and seeks to make any potential for data value creation visible that has not yet have been exploited.
Find further information and the slides of the lectures here.
Due to the size and volume of unstructured textual data, automatic processing techniques are desired by many researchers in business and economic studies. A common use case is the data scraped from Internet. Researchers can process it using the algorithm called named entity linking. It finds concepts in texts (e.g., organisations, persons and locations) and links these concepts to entities in a knowledge base.
Let’s apply spaCyOpenTapioca to the sentence “Christian Drosten works in Charité, Germany.”. It correctly identifies Christian Drosten as a person with Wikidata ID Q1079331, Charité as organisation with Q162684 and Germany as location with Q183. Visualisation of results is also possible:
Sudden and unforeseen shocks can cause incalculable and fast-changing economic dynamics to which policy makers need to respond quickly – as we have experienced during the COVID-19 pandemic. At the same time, data from traditional statistics that usually guide policy decisions are only available with non-negligible time delays. This leaves policy makers uncertain about how to most effectively manage their economic countermeasures to support businesses.
Given this information deficit, our colleagues from ZEW – Leibniz Centre for European Economic Research propose a framework that guides policy makers throughout all stages of an unforeseen economic shock by providing timely and reliable data as a basis to make informed decisions. They do so by combining early stage ‘ad hoc’ web analyses, ‘follow-up’ business surveys, and ‘retrospective’ analyses of firm outcomes.
Learn more about the proposed integrated data framework in the recently published discussion paper.
Company websites are an important source of economic data and can be used for various scientific approaches, such as predicting firm innovativeness or examining market entry strategies. But the content of those websites changes over time, which requires a continuous monitoring to capture this (change of) information.
Working with data involves attention to data privacy issues in order to protect the individual. But for researchers it can be very demanding to identify which privacy protection regulation is binding and under which conditions it applies to their own work as legal issues are usually not central to their area of expertise.
To offer researchers and other people working with data an entry point to understand those important privacy law issues, the BERD@BW team developed an interactive Virtual Assistant (iVA). iVA leads you with a series of questions through the regulations and provides a result based on your answers.
BERD@BW: interactive Virtual Assistant (iVA) helps researchers to understand data privacy regulations
The first part of iVA, which examines with you if privacy protection regulations apply to your data project, was recently updated and can be accessed here: https://www.berd-bw.de/iva/(german)
While iVA currently addresses if privacy protection regulations apply to you, we are already working on an extension to cover the issue more profoundly. We are looking forward to present you a second part of iVA, that will let you check if you are allowed to process personal data and what requirements you have to keep in mind.
We are excited that our “big sister” BERD@NFDI was accepted for funding within the National Research Data Infrastructure (NFDI) starting October 2021. The BERD@NFDI funding gives us the opportunity to lift BERD@BW to the next level and to sustainably develop and build a national cloud-based platform for FAIR Business, Economics and Related Data that reflects the whole data analytics pipeline. Of course, the BERD@BW services will also be accessible through BERD@NFDI. Follow BERD@NFDI on Twitter and LinkedIn to stay up to date.
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