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724 results for “Germans”
GeoERA RESOURCE H3O-PLUS data set which contains hydraulic properties of prime aquifers and aquitards in the Dutch-Flemish-German cross-border area
<p>Dataset which contains information about hydraulic properties of harmonized hydrogeological units in the Dutch-Flemish-German cross-border region which was compiled in the GeoERA RESOURCE project under WP3 H3O-PLUS. The harmonization of the 3D geometry of the cross-border hydrogeological units in the H3O projects constituted a major step towards a common hydrogeological dataset of the Roer Valley Graben and thus the harmonization of groundwater flow models. The database that was compiled provides the characterization of these hydrogeological units with respect to their hydraulic properties, primarily their hydraulic conductivity.<br> The associated report and appendices describe the database of hydraulic properties of aquifers and aquitards based on common criteria. Attention is also given to the characterization of hydraulic properties of faults.</p>
The Bomber's Baedeker. A Guide to the Economic Importance of German Towns and Cities
<p>The Bomber's Baedeker</p> <p>The two-volume printed work “The Bomber's Baedeker. A Guide to the Economic Importance of German Towns and Cities” was produced during the Second World War by the British Foreign Office and the Ministry of Economic Warfare. It lists towns and cities of the German Reich with more than a thousand inhabitants and information on their war-related infrastructure, industrial and production facilities. Only four verified copies still exist worldwide and none of them have been accessible for scholarly digital use until now. “The Bomber's Baedeker” was re-discovered in 2019 in the library of the Leibniz Institute of European History (IEG), digitised in cooperation with the Mainz University Library and made accessible and processed by the Digital Historical Research | DH Lab and the Darmstadt University of Applied Sciences as part of a cross-institutional cooperation (including courses with students) so that “The Bomber's Baedeker” can now be used, analysed and processed as an open, machine-readable data source in compliance with FAIR principles.</p>
German Climate Change Tweet Corpus (GerCCT)
<p>First release of the GerCCT Corpus, a German tweet resource annotated for argument components, argument properties, sarcasm and toxic language.</p> <p>The corpus consists of 1,200 tweets and its annotations. Each tweet is associated with its respective source tweet, i.e. the tweet it replies to. Source tweets were used to provide annotators with additional context. The annotations refer to the reply tweet, i.e. NOT to the source tweet. For copyright reasons we cannot distribute the actual tweet content. Instead we share the source and reply tweet IDs and the annotations.</p> <p>The current version includes class annotations on the document level, i.e. on the tweet level. We are working on creating the respective span annotations.</p>
Metadata and annotation data for the XSample corpus on German academic language
<p>The XSample corpus war created in the project <em>XSample</em> (https://www.izus.uni-stuttgart.de/fokus/fdm-projekte/xsample/) at Universität Stuttgart in 2021 by Melanie Andresen and Axel Pichler. It contains 135 German academic journal articles, 45 each from the disciplines linguistics, literary studies and philosophy. The texts themselves cannot be made public for copyright reasons. However, metadata and some annotation data are published here.</p> <p><strong>xsample-metadata.csv</strong><br> This file contains metadata on the texts in the corpus, like journal, title, authors, text length, and the URL to the original paper. It also contains two analytical metrics, 'past-ratio' and 'temp-expr-ratio', that are based on the annotations in the other two files. The variable 'past-ratio' expresses the proportion of verbs in past tense relative to all finite verbs in the text. The variable 'temp-expr-ratio' gives the number of temporal expressions per 1000 token.</p> <p><strong>xsample-heidel.csv</strong><br> This file contains all temporal expressions found and classified by the annotation tool <em>HeidelTime</em> (https://github.com/HeidelTime/heideltime, V. 2.2.1, Strötgen & Gertz 2013 ). The variable 'position' expresses the position of the first character of the temporal expression in the text in characters.</p> <p><strong>xsample-sticker2.csv</strong><br> This file contains all finite verbs found and classified by the annotation tool <em>sticker2</em> (https://github.com/stickeritis/sticker2). The variable 'position' expresses the position of the first character of the finite verb in the text in characters.</p> <p><strong>References</strong><br> Strötgen, Jannik & Michael Gertz. 2013. Multilingual and cross-domain temporal tagging. <em>Language Resources and Evaluation</em>. Springer 47(2). 269–298. <a href="https://doi.org/10.1007/s10579-012-9179-y">https://doi.org/10.1007/s10579-012-9179-y</a>.</p> <p> </p>
Polifonia Corpus - Periodicals Module Metadata - German Language
<p>We release the Metadata of the Periodicals module of the Polifonia Textual Corpus. According to the availability from the source origin, the Metadata may include the URL from which a text of the Books corpus is accessible, along with the title, the author, the year of publication, and the publisher. Metadata allows for a complete reconstruction of the corpus as we cannot make the actual texts available because they are subject to heterogeneous licensing.</p>
Reference Data Set: Electricity, Heat, and Gas Sector Data for Modeling the German System
<p>This reference data set representing the status quo of the German electricity, heat, and natural gas sectors was compiled within the research project ‘LKD-EU’ (Long-term planning and short-term optimization of the German electricity system within the European framework: Further development of methods and models to analyze the electricity system including the heat and gas sector).</p> <p>While the focus is on the electricity sector, the heat and natural gas sectors are covered as well. With this reference data set, we aim to increase the transparency of energy infrastructure data in Germany. Where not otherwise stated, the data included in this report is given with reference to the year 2015 for Germany. The data set is documented in DIW Data Documentation 92 (see references).</p> <p>The project is a joined effort by the German Institute for Economic Research (DIW Berlin), the Workgroup for Infrastructure Policy (WIP) at Technische Universität Berlin (TUB), the Chair of Energy Economics (EE2) at Technische Universität Dresden (TUD), and the House of Energy Markets & Finance at University of Duisburg-Essen. The project was funded by the German Federal Ministry for Economic Affairs and Energy through the grant ‘LKD-EU’, FKZ 03ET4028A-D.</p>
Research data management in the German-speaking Sports Sciences - Survey on the Status Quo
<p>The data set contains survey data on the status quo of research data management within the German-speaking sports science community. The survey was conducted as an online survey in the period from August 16<sup>th</sup> to September 30<sup>th</sup>, 2023.</p>
German Student Responses to Probability Theory and Statistics Bachelor Course (WuS24): Evaluated with Rubrics
<p><strong>Description:</strong></p> <p>This dataset contains questions and answers from an introductory computer science bachelor course on statistics and probability theory at Hochschule Bonn-Rhein-Sieg. The dataset includes three questions and a total of 90 answers, each evaluated using binary rubrics (yes/no) associated with specific scores.</p> <p> </p> <p><strong>Dataset Components:</strong></p> <ol> <li><em>questions.csv</em>: Contains the details of the three questions. <ul> <li>Columns: <ul> <li><em>question_id</em>: Unique identifier for each question</li> <li><em>question</em>: The text of the question</li> <li><em>solution</em>: The reference answer for the question</li> <li><em>max_score</em>: The maximum score for this question</li> </ul> </li> </ul> </li> <li><em>rubrics.csv</em>: Contains the grading rubrics for each question. <ul> <li>Columns: <ul> <li><em>question_id</em>: Unique identifier for each question</li> <li><em>rubric_id</em>: Unique identifier for each rubric within a question</li> <li><em>rubric</em>: The rubric phrased as a question</li> <li><em>score</em>: The score associated with fulfilling the rubric</li> </ul> </li> </ul> </li> <li><em>answers.csv</em>: Contains 90 student answers to the questions. <ul> <li>Columns: <ul> <li><em>answer_id</em>: Unique identifier for each answer</li> <li><em>question_id</em>: Unique identifier of the question that is answered</li> <li><em>answer</em>: The text of the student's answer</li> <li><em>score</em>: The score associated with fulfilling the rubric</li> </ul> </li> </ul> </li> <li><em>answer_rubrics.csv</em>: Contains the evaluations of rubrics for each answer.<br> <ul> <li>Columns: <ul> <li><em>answer_id</em>: The identifier of the answer.</li> <li><em>question_id</em>: The identifier of the question.</li> <li><em>rubric_id</em>: The identifier of the rubric for that question.</li> <li><em>label</em>: Indicates if the rubric crierion is fulfilled for the specific answer (true / false).</li> </ul> </li> </ul> </li> </ol> <pre><strong><br>Working with the Dataset:</strong> The easiest way to work with this dataset is using the class `RubricsDataset` defined in the file `dataloader.py`. Example:<br><br></pre> <pre><code>from dataloader import RubricsDataset<br><br>dataset = RubricsDataset.from_directory("data")<br> dataset.get_question(1) # Get a dictionary containing info about the first question, including rubrics dataset.get_answers(1) # Get all the answers for the first question as a list. Each answer is a dictionary with answer, score, rubrics.</code></pre>
Mass mortality among colony-breeding seabirds in the German Wadden Sea in 2022 due to distinct genotypes of HPAIV H5N1 clade 2.3.4.4b: data sets on phylogeographic analyses
<p>Highly pathogenic avian influenza viruses (HPAIV) of clade 2.3.4.4b of the H5 goose/Guangdong (gs/GD) lineage have repeatedly emerged in Germany since 2016. Both poultry holdings and wild birds have been heavily hit but the 2020-2021 and 2021-2022 HPAI winter seasons exceeded all previously recorded epizootics in Germany in terms of number of wild bird cases recorded, genetic diversity of viruses, and duration of virus activity. In past seasons regional massing of wild bird cases were seen at the German coasts of the Baltic and North Sea, but species mainly affected varied from season to season. In 2022 a new and, in Europe, unprecedented aspect was observed when several cormorant and seabird breeding colonies became affected since May at the Baltic Sea coast and in the Wadden Sea, respectively by HPAI H5N1 viruses.</p> <p> </p>
Collection of Middle High German Rubrics in Miscellany Manuscripts 12th-16th centuries
<p>This is a collection of Middle High German Rubrics from miscellany manuscripts. </p> <p>The corpus for this study comprises almost 1432 rubrics from 68 manuscripts, which correspond to over 800 different works. It was compiled manually using different sources. One important source were previous monographs that catalogued texts and rubrics in manuscripts (see bibliography). For less researched sources, library catalogues and digital manuscript facsimili were consulted. This is not an exhaustive corpus of Middle High German rubrics for <em>Reimpaargedichte</em>, but it has all the most important manuscripts and is very representative.</p> <p> </p> <p><strong>Files</strong></p> <p>rubrics.csv: Main file, list of rubrics with reference to the modern title of the literary work to which they correspond and the manuscript. Titles are in paleographic transcription (without abbreviations) and lemmatised.</p> <p>works.csv: A list of all the works refered in the rubrics.csv file with information about author and genre</p> <p>manuscripts.csv: A list of manuscripts mentioned in rubrics.csv. Contains information about date of composition and language.</p> <p> </p> <p> </p> <p><strong>Bibliography:</strong></p> <p>Dahm-Kruse, Margit. <em>Die Sammlung als Kontext. Formen der Retextualisierung und Kontextualisierung mittelhochdeutscher Versnovellen in kleinepischen Sammelhandschriften am Beispiel von Konrads von Würzburg “Herzmaere”</em>. Tübingen: Narr Francke Attempto, 2018.</p> <p>Klingner, Jacob, y Ludger Lieb. <em>Handbuch Minnereden</em>. Berlin, Boston: De Gruyter, 2013.</p> <p>Mihm, Arend. <em>Überlieferung und Verbreitung der Märendichtung im Spätmittelalter.</em> Heidelberg: Winter, 1967.</p> <p>Moelleken, Wolfgang Wilfried. <em>Die Kleindichtung des Strickers</em>. 5 vols. Göppingen: Kümmerle, 1973.</p>
Query auto-completions for German politicians of the 18th Bundestag
<p><strong>bundestag.csv</strong> - UTF-8 encoded comma separated text file</p> <p>This dataset contains the members of the 18th German Bundestag in the constitution of late 2016.</p> <p><Name>: name of the politician</p> <p><Born>: birthday</p> <p><Party>: party membership of the politician</p> <p><Bundesland> state of the politician</p> <p><Gender> gender of the politician</p> <p><Age> age of the politician (as of 2017)</p> <p><Cluster 3> number of unique auto-completions assigned to topic: "location information"</p> <p><Cluster 2> number of unique auto-completions assigned to topic: "personal and emotional"</p> <p><Cluster 1> number of unique auto-completions assigned to topic: "politics and economics"</p> <p><Total> total number of unique auto-completions</p> <p> </p> <p><strong>terms.csv </strong>- UTF-8 encoded comma separated text file</p> <p>This dataset contains the unordered and pooled auto-completions for the German politicians from Bing search (http://api.bing.net/osjson.aspx), from Duck-Duck-Go (https://duckduckgo.com/ac/) and from Google search (http://clients1.google.de/complete/search). The data was crawled on (mostly) two times per day from 2017/02/03 to 2017/06/19. German language settings were used for Google and Bing, English language setting was used for Duck-Duck-Go. The API requests were sent with an IP address from Cologne, Germany. </p> <p><source>: google, bing or ddg</p> <p><queryterm>: the query term, matches the name of the politican in the file <bundestag.csv></p> <p><suggestterm>: the suggested query auto-completion</p>
List of Digital Resources for Medieval Studies in German-speaking Countries
<p>The Middle Ages have been brought into the digital era through the extensive digitisation of medieval source material, transforming the scope and breath of medieval studies. The field has long embraced digital methodologies, with medievalists praised as early adopters since the 1940s. German-speaking countries have brought forward innovative projects ranging from digital editions, interactive maps, to comprehensive databases and computational analysis.</p> <p>The following pages present a curated list of 164 digital resources and repositories for medieval studies that are initiated or located in Germany, Austria, and Switzerland. The list is not comprehensive and ongoing. It was made to aid scholars in navigating the dynamic landscape of digital medieval studies, promoting collaboration and providing insight into the field's development. The selected projects are supportive resources dealing with the Middle Ages (up to 1500) and have a clear research goal. It covers diverse topics like numerology, heraldry, monastic life, and architecture. Most of the listed digital resources are freely accessible.</p> <p>The projects are classified by their <em>digital methods</em>, as described in more detail on a separate page. The <em>descriptors</em> and <em>types</em> used to describe the projects distinctly highlight the interdisciplinary nature of medieval studies in the digital age. This list emphasises the transformative potential of digital resources, offering a starting point for continued exploration and expansion in the evolving landscape of digital medieval studies.</p> <p><br>This repository is created within the sub project <a href="https://www.virtuelle-lebenswelten.de/forschung/wissen" target="_blank" rel="nofollow noreferrer noopener">B02 <em>Virtuelles Mittelalter</em></a>, curated by Juliet Diekkämper with the help of Suzette van Haaren. Sources gathered in 2023-2024.</p>
German CBOW FastText embeddings with min count 250
<p>FastText embeddings built from Common Crawl german dataset</p> <table> <caption>Parameters</caption> <thead> <tr> <th scope="col">Parameters</th> <th scope="col">Value(s)</th> </tr> </thead> <tbody> <tr> <td>Dimensions</td> <td>256 and 384</td> </tr> <tr> <td>Context window</td> <td>5</td> </tr> <tr> <td>Negative sampled</td> <td>10</td> </tr> <tr> <td>Epochs</td> <td>1</td> </tr> <tr> <td>Number of buckets</td> <td>131072 or 262144</td> </tr> <tr> <td>Min n</td> <td>3</td> </tr> <tr> <td>Max n</td> <td>6</td> </tr> </tbody> </table>
btw17 query auto completion - query suggestions for German politicians and parties before the federal election 2017
<p>The dataset contains the query suggestions for 5 major German parties (terms: "afd", "csu", "dielinke", "fdp", "grüne", "spd") and ten popular politicians and party leaders (terms: "Alexander Gauland", "Alice Weidel", "Angela Merkel", "Cem Özdemir", "Christian Lindner", "Dietmar Bartsch", "Katrin Göring-Eckardt", "Martin Schulz", "Sahra Wagenknecht").</p> <p>The data was crawled on (mostly) two times per day from Tue Aug 04, 2017 to Tue Oct 31, 2017. The dataset contains 20001 suggestions from Bing search (http://api.bing.net/osjson.aspx), 11935 suggestions from Duck-Duck-Go (https://duckduckgo.com/ac/) and 33521 suggestions from Google search (http://clients1.google.de/complete/search). Note, that for some terms and dates no suggestions were returned by some of the APIs.</p> <p>German language settings were used for Google and Bing, English language setting was used for Duck-Duck-Go. The API requests were sent with an IP address from Cologne, Germany. </p> <p>The UTF-8 encoded comma separated text file contains the following columns:</p> <p><source>: google, bing or ddg</p> <p><queryterm>: the query term</p> <p><date>: the date and time of the API call formatted as ISO8601</p> <p><suggestterm>: the suggested query completion (the query term was removed from the suggestion)</p> <p><position>: the position of the query suggestion within the list returned by the API (ranges from 0 to 19)</p> <p> </p> <p> </p> <p><br> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Data set of German coal power stations for coal phase out auctions
<p>This repository contains the coal power station data set used in the paper "Auctions to phase out coal power: Lessons learned from Germany" by Silvana Tiedemann and Finn Müller-Hansen, published in Energy Policy in 2023. All details about the data set are provided in the readme.md.</p> <p> </p>
Mapping of districts to control zones of German Transmission System Operators (TSOs)
<p><strong>Mapping of districts to control zones of German Transmission System Operators (TSOs)</strong></p> <p>This dataset provides a mapping of districts in Germany at NUTS3 level to control zones that are maintained by four transmission system operators (50Hertz, Amprion, TenneT, TransnetBW). A visualisation of the mapping is provided it GER_NUTS3_TSOs.png.</p> <p>I can provide no guarantee of the accuracy or completeness of the provided information. In case the control zones of the TSOs change, or an error is detected, I do not assume liability for the error. The output file(s) can also be re-generated with the provided python script (GER_NUTS3_TSOs.py), and manipulated if necessary. In case you detect an error, please reach out to me so we can correct it in order to provide as accurate information as possible.</p> <p><strong>Licensing</strong></p> <p>This dataset is created on top of a dataset of German political administrative boundaries at NUTS3 level covering Germany provided by geoBoundaries (DEU_ADM2.shp). geoBoundaries is an online, open license database of global political administrative boundaries (i.e., state, county). For further information, see https://www.geoboundaries.org/.</p> <p>For the processing, I am also using the dataset "Verwaltungsgebiete 1:2500000" (vg_12500.shp) provided by the "Bundesamt für Kartographie und Geodäsie". The dataset is licensed as "Data licence Germany - attribution - version 2.0", and can be retrieved at https://gdz.bkg.bund.de/index.php/default/verwaltungsgebiete-1-2-500-000-stand-31-12-vg2500-12-31.html. A reference to the license is provided under the following link: https://www.govdata.de/dl-de/by-2-0.</p> <p>The files GER_NUTS3_TSOs.png, GER_NUTS3_TSOs.shp, GER_NUTS3_TSOs.shx, GER_NUTS3_TSOs.prj, GER_NUTS3_TSOs.dbf and GER_NUTS3_TSOs.cpg are released under the Creative Commons 4.0 Attribution International (CC BY 4.0).</p> <p>The file GER_NUTS3_TSOs.py is released under a MIT license.</p>
childPoeDE: A corpus of German Children's Poems for Computational and Experimental Studies - Metadata
<p>The childPoeDE corpus is a collection of 1082 German poems for children created within the CHYLSA project. The poems were taken from anthologies published between 1991 and 2019. This publication includes the poem-level metadata for each poem with information about the author, the poem's length, data on case, punctuation, layout, rhyme, type-token ratio (TTR and MATTR) and lexical density. It also includes token-level metadata, namely word length and position, POS tags in different levels of granularity as well as data on onomatopoeia and sonority. Furthermore, this publication provides a word frequency table and a Python script which was used to extract some of the metadata from the texts (poemtool.py). The childPoeDE corpus does not contain all poems from the anthologies. A list of the poems that have been omitted for different reasons (length, language, typography, ...) can be accessed as well.</p> <p>Read more about the childPoeDE corpus in our data paper published in the Journal of Open Humanities Data: <a href="https://doi.org/10.5334/johd.102">The ChildPoeDE Corpus: 1082 German Children’s Poems for Computational and Experimental Studies on Poetry Reception</a>.</p> <p>DFG Schwerpunktprogramm SPP 2207 “Computational Literary Studies“<br> Online:</p> <ol> <li><a href="https://gepris.dfg.de/gepris/projekt/402743989">https://gepris.dfg.de/gepris/projekt/402743989</a></li> <li><a href="https://dfg-spp-cls.github.io/">https://dfg-spp-cls.github.io<em>/</em></a></li> </ol> <p>Subproject: „CHYLSA (Children’s and Youth Literature Sentiment Analysis)“</p> <p>Online:</p> <ol> <li><a href="https://gepris.dfg.de/gepris/projekt/424250469">https://gepris.dfg.de/gepris/projekt/424250469</a></li> <li><a href="https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-CHYLSA/">https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-CHYLSA/</a></li> </ol>
Result data related to "Tröndle et al (2023): Public preferences for phasing-out fossil fuels in the German building and transport sectors"
<p>Parameter estimations from the conjoint experiments performed in "Tröndle et al (2023): Public preferences for phasing-out fossil fuels in the German building and transport sectors". Parameter estimations are given for different:</p> <p>* estimands: average marginal component effects (amce) or marginal means,</p> <p>* variables: choice and rating,</p> <p>* sectors: buildings (heat) and transport sector,</p> <p>* subgroups: by-<subgroupname>.</p> <p>Filenames accordingly are: <estimand>-<variable>-<sector>.csv or <estimand>-<variable>-<sector>-by-<subgroup>.csv</p>
H2020 Platone German Demonstrator - Use Case Setting Data
<p>This dataset belongs to the German demonstrator of the H2020 Platone project (WP5). The dataset contain information that have been set for Use Cases (UCs) parameterization during the project phase. UC have been parameterized along a grafical user interface (GUI) named "Use Case Selector". Each parameterized UC triggered has been logged in the dataset.</p> <p><strong>Background - Field Test Setup</strong></p> <p>The field test setup consists of a Low Voltage (LV) community with 450 kW installed generation capacity. The power exchange between the LV grid and Medium Voltage (MV) grid takes place along a single point of common coupling (PCC). i.e., a secondary substation that includes a transformer with senors on the LV busbar, to measure the net power exchange. The community consists of 89 households, 450kW of installed PV generation capacity, a Community Battery Energy Storage (CBES) connected to the LV busbar with 300 kW and 850 kWh capacity. </p> <p><strong>Definition of data:</strong></p> <p><strong>RequID</strong> - Request ID - Identifier for each triggered UC</p> <p><strong>Alert</strong> - Indicates, whether UC has been executed successfull ( " "and " true" indacates successfull implementation by Energy Management System (EMS); "false" indicates that UC has not been implemented by EMS)</p> <p><strong>Submission -</strong> timestamp of UC submission<strong> </strong></p> <p><strong>Note -</strong> Annotations entered by UseCase operator</p> <p><strong>Priority -</strong> Defines UC priority set by operator (priority: 1 - high , 2 - medium, 3 - low, 4 - very low) (only relevant for UC 2)</p> <p><strong>Status - </strong>Indicates the status of the UC (closed - UC has been executed, cancelled, UC has been has been canceled before or during application)</p> <p><strong>Start</strong> - Point of time set for the beginning of UC</p> <p><strong>End</strong> - Point of time set for the end of UC</p> <p><strong>Type</strong>- Triggered Type of UC (1 - "Virtual Islanding of LV community" (UC 1); 2 - "Coordination of Flex Request" (UC 2); 3 - "Energy Import in Bulk" (UC 3); 4 - "Bulk-based Energy Export" (UC 4)</p> <p><strong>Subtype</strong> - 0 - Rule-Based Operation Mode with 15-minutes control cycles of battery (CBES in the field) ;1 - Day-ahead forecast-based control; 2.0 - Schedule-based operation mode with optimization applied to a day-ahead forecast (optimization target: minimization of power exchanges at MV/LV PCC within 24h period ; 21 - Schedule-based operation mode with optimization applied to a day-ahead forecast (optimization target: minimization of power exchanges at MV/LV PCC and achieving a requested State of Charge (of CBES) at the end of UC_End;</p> <p><strong>bulkStart</strong> - Point of time of start of energy bulk import or export (only relevant for UC 3 and 4)</p> <p><strong>bulkEnd</strong> - Point of time of end of energy bulk import or export (only relevant for UC 3 and 4)</p> <p><strong>bulk Energy</strong> - Amount of energy triggered to be imported or exported as bulk (only relevant for UC 3 and 4)</p> <p><strong>Final_SOF </strong>- State of Charge (SOC) of CBES that should be achieved at end of UC (End)</p> <p><strong>FlexDemand </strong>- Requested power exchange that should be achieved at MV/LV PCC (Only relevant for UC 2)</p> <p><strong>Ptcb - </strong>Measured CBES charging power at poin of time of UC submission </p> <p><strong>Ptei </strong>- Measured power exchange at PCC at point of time of UC submission </p> <p><strong>SoC </strong>- State of Charge of CBES at point of time of UC submission </p> <p><strong>SoE</strong> - State of Energyof CBES at point of time of UC submission </p> <p><strong>ActiveSet </strong>- State of Energyof CBES at point of time of UC submission </p> <p><strong>maxSoC </strong>- Maximum SoC set for CBES at point of time of UC submission </p> <p><strong>minSoc - </strong>MinimumSoC set for CBES at point of time of UC submission </p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 864300.</p>
German Political Speeches Corpus
<p>This text archive focuses on German political speeches held by top officials mostly from 1990 onwards, selected according to their political relevance. The currently included speeches come from the following sources:</p> <ul> <li>Official pages of the German <a href="http://www.bundespraesident.de/EN/Home/home_node.html">Presidency</a>, <a href="https://www.bundeskanzlerin.de/Webs/BKin/EN/Chancellery/federal_chancellery_node.html">Chancellery</a>, <a href="http://www.bundestag.de/en/parliament/presidium/function_neu">Bundestag</a>, <a href="https://www.auswaertiges-amt.de/en/">Ministry of Foreign Affairs</a></li> <li>Personal pages of the <a href="https://www.helmut-kohl.de/dokumente_reden.html">Helmut Kohl archive</a>, <a href="http://www.thierse.de/reden-und-texte/reden/">Wolfgang Thierse</a> and <a href="http://www.norbert-lammert.de/01-lammert/texte.php">Norbert Lammert</a></li> </ul> <p>This resource is available online:</p> <ul> <li><a href="https://www.dwds.de/r?corpus=politische_reden">Online queries on the DWDS website</a> and <a href="https://www.dwds.de/d/korpussuche">usage instructions</a> (the text base may be newer than the downloadable archives)</li> <li><a href="http://purl.org/corpus/german-speeches">http://purl.org/corpus/german-speeches</a></li> </ul> <p>The files below consist of texts with metadata encoded in <a href="http://xml.silmaril.ie/whatisxml.html">XML format</a>. For appropriate tooling see:</p> <ul> <li>Python tutorial using the speeches: <a href="https://www.timmer-net.de/2019/03/24/nlp_basics/">Natural Language Processing — Einsteigen und Loslegen!</a></li> <li><a href="http://www.corpusexplorer.de">CorpusExplorer</a>, corpus linguistics and text mining software featuring the speeches</li> <li><a href="https://github.com/adbar/german-nlp">List of off-the-shelf NLP tools for German</a></li> </ul> <p>This is work in progress, updated and extended versions will follow.</p>
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