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  • Digital Humanities and Cultural Heritage
  • 2024-2024
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  • Authors: Leclère, Antoine; Silan, Marie-Sophie;
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    Authors: Nurcahya, Yan;

    Abstract: Humans as historical living creatures, only humans can make history. All human activities form a cultural system, while culture as human action (actus humanus) is always related to future plans. The idea of progress is something that cannot be separated from the history of human life. Humans with the idea of life and progress have changed their natural world to become more comfortable to live in. Humans live their lives with three dimensions of time; past time, present time and future time. Humans not only do what they want, but also decide what they want to do. So when we discuss history, we don’t just say that everything in society is rooted in the past. Keywords: Ideas, Principles, Philosophy, History

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    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Dataset . 2024
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      Dataset . 2024
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    Authors: Bimantara, I Made Satria;

    This dataset consists of 120 Balinese story texts (as known as Satua Bali) which have been annotated for character analysis purposes, including character identification, alias clustering, and character classification into protagonist or antagonist. The labeling involved two Balinese native speakers who were fluent in understanding Balinese story texts. One of them is an expert in the fields of sociolinguistics and macrolinguistics. Reliability and level of agreement in the dataset are measured by Cohen's kappa coefficient, Jaccard similarity coefficient, and F1-score and all of them show almost perfect agreement values (>0,81). There are four main folders, each used for different character analysis purposes: 1. First Dataset (charsNamedEntity): 89,917 tokens annotated with five character named entity labels (ANM, ADJ, PNAME, GODS, OBJ) for character named entity recognition purpose 2. Second Dataset (charsExtraction): 6,634 annotated sentences for the purpose of character identification at the sentence level 3. Third Dataset (charsAliasClustering): 930 lists of character groups from 120 story texts for the purpose of alias clustering 4. Fourth Dataset (charsClassification): 848 lists of character groups that have been filtered into two groups (Protagonist and Antagonist)

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    Dataset . 2024
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    Data sources: Datacite
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    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Dataset . 2024
      License: CC BY
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      Mendeley Data
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Miranda, Bella;

    This is a parallel corpus dataset in which each sentence has a corresponding pair. This dataset is specifically created to facilitate the use of machine learning in the field of translation. The dataset is meticulously compiled to encompass various contexts and topics, enabling users to expand their understanding of the use of everyday language, language variations, as well as expressions and typical idioms from both languages. This dataset is independently compiled, with a total of 5261 sentences formed through the collection of online sources for the Indonesian language. Additionally, it utilizes the Malay language dictionary from the Bengkulu library, located in the city of Bengkulu, Bengkulu Province, Indonesia.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: USB, Educación y Humanismo;

    Objetivo: Analizar la incidencia de la reformulación del Proyecto Ambiental Escolar (PRAE) en la educación para una ciudadanía ambiental en la escuela colombiana. Metodología: La investigación se desarrolló desde un enfoque cualitativo con la metodología de la Investigación-Acción-Participativa, teniendo como fundamento la perspectiva de Fals Borda. La población estuvo conformada por 11 estudiantes, 4 docentes, 22 padres de familia y 5 líderes comunitarios de una institución educativa. En total participaron 43 personas (21 mujeres, cifra que corresponde al 48,8% de la población estudiada, y 22 hombres, es decir el 51,2% de dicha población). Resultados:El PRAE se asume como unapolítica del discurso para el cumplimiento de la normatividad educativa, más que una acción con-sentida—apropiada por toda la comunidad académica—. Además, se establece una estrategia pedagógica de ciudadanía ambiental mediante la reformulación participativa del PRAE. Conclusiones:La reformulación colectiva fortalece los mecanismos de participación ciudadana y empoderamiento de toda la comunidad educativa para generar propuestas en su territorio desde una visión crítica; camino aún de largo aliento en muchas instituciones educativas.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Dataset . 2024
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      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ramadhani, Dimas Gilang;

    The training dataset designed for understanding and solving chemical calculations, specifically calculating the mass of compounds given the number of moles and molar mass, is a foundational resource for training NLP models in the deep learning domain. This dataset aims to equip models with the ability to accurately interpret and execute chemical calculations presented in textual form. Structured to support the training of advanced NLP models like BERT, GPT, or other transformer-based models, it comprises a series of calculation questions, numerical data for moles and molar mass, and the expected answers in units of mass. Each entry is annotated with additional information such as the calculation category, the formula used, and step-by-step explanations to facilitate model understanding. Presented in the JSON Lines (jsonl) format, this structured approach enables efficient batch processing and individual item analysis, making it an invaluable tool for developing NLP applications capable of performing quantitative chemical problem-solving. The application of this dataset extends beyond mere calculation to include natural language understanding within the context of chemistry, extracting numerical and contextual information, and generating human-comprehensible textual answers. Post-training, models are evaluated against a separate test dataset to ensure their capability to comprehend questions, extract relevant data accurately, and produce precise numerical answers. Evaluation metrics such as accuracy, precision, and recall in question understanding, along with the numerical accuracy of answers, demonstrate the model's performance. This dataset not only facilitates the research and development of NLP models that apply chemical knowledge to solve quantitative problems but also significantly advances AI's role in chemical education and research.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Dataset . 2024
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      Data sources: Datacite
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      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Stocker, Alan;

    The total returns, together with yield and duration, of UK gilts sectors (i.e., gilts with maturities under 5 years, from 5 to 15 years, over 15 years, etc.) have been calculated using the historical prices, coupons and amounts outstanding of individual gilts for years since 1870. The full method is described in Stocker A.J. (2024). “Total Returns for UK Gilt Sectors of Different Maturities from 1870 Onwards”, Available at SSRN: https://ssrn.com/abstract=4742450 or http://dx.doi.org/10.2139/ssrn.4742450. A full description of the dataset can be found in the readme.txt file.

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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Dataset . 2024
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      Dataset . 2024
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  • Authors: Pandya, Mugdha; Bontcheva, Kalina; Maynard, Diana;

    This is a dataset with tweets from X. Each tweet mentions one or more UK MPs from a subset selected for our study to give a diverse representation of political leanings. Each tweet is labelled for hostility and the identity characteristic it targets (religion, race, gender). Each annotator also provides a confidence score for each label. Three annotators annotate each tweet. Annotators are UK-based students from Computer Science and Politics.

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    ZENODO
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    ZENODO
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    Authors: de Pater, Catharina;

    Tables underlying the analyses for De Pater, C., Verschuuren, B., Greil, S., Wals, A., 2024. Exploring spiritual values in Forest Management Practices in the Netherlands. Trees, Forests and People Trees, Forests and People 100522. https://doi.org/10.1016/j.tfp.2024.100522.

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    Authors: Lloyd, Montgomery; Clara, Lüders; Walid, Maalej;

    These artefacts accompany the "Mining Issue Trackers: Concepts and Techniques" chapter within the "Handbook of Natural Language Processing for Requirements Engineering" book. The book chapter includes a "Use Cases" section where natural language processing (NLP) techniques are applied to issue tracker data from Montgomery et al. [1]. The JupyterNotebooks in this replication package can be used to follow along with the use cases in the chapter. Lloyd Montgomery - lloyd.montgomery@uni-hamburg.deDr. Clara Lüders - clara.marie.lueders@gmail.comProf. Dr. Walid Maalej - walid.maalej@uni-hamburg.de All authors are affiliated with the University of Hamburg in Hamburg, Germany. Please cite this work as: Montgomery L, Lüders C, Maalej W. of Part, "Mining Issue Trackers: Concepts and Techniques," in "Handbook of Natural Language Processing for Requirements Engineering", 1st Edition, Ferrari A, Deshpande G. Eds. Springer Nature Switzerland AG, Cham, Switzerland, 2024, to appear. Title of Chapter: "Mining Issue Trackers: Concepts and Techniques" Abstract of the Chapter: An issue tracker is a software tool used by organisations to interact with users and manage various aspects of the software development lifecycle. With the rise of agile methodologies, issue trackers have become popular in open and closed-source settings alike. Internal and external stakeholders report, manage, and discuss “issues”, which represent different information such as requirements and maintenance tasks. Issue trackers can quickly become complex ecosystems, with dozens of projects, hundreds of users, thousands of issues, and often millions of issue evolutions. Finding and understanding the relevant issues for the task at hand and keeping an overview becomes difficult with time. Moreover, managing issue workflows for diverse projects becomes more difficult as organisations grow, and more stakeholders get involved. To help address these difficulties, software and requirements engineering research have suggested automated techniques based on mining issue tracking data. Given the vast amount of textual data in issue trackers, many of these techniques leverage natural language processing. This chapter discusses four major use cases for algorithmically analysing issue data to assist stakeholders with the complexity and heterogeneity of information in issue trackers. The chapter is accompanied by a follow-along demonstration package with JupyterNotebooks. [1] Montgomery, L., Lüders, C., Maalej, W.: An alternative issue tracking dataset of public jira repositories. In: Proceedings of the 19th International Conference on Mining Software Repositories. pp. 73–77 (2022)

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    ZENODO
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    ZENODO
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  • Authors: Leclère, Antoine; Silan, Marie-Sophie;
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    Authors: Nurcahya, Yan;

    Abstract: Humans as historical living creatures, only humans can make history. All human activities form a cultural system, while culture as human action (actus humanus) is always related to future plans. The idea of progress is something that cannot be separated from the history of human life. Humans with the idea of life and progress have changed their natural world to become more comfortable to live in. Humans live their lives with three dimensions of time; past time, present time and future time. Humans not only do what they want, but also decide what they want to do. So when we discuss history, we don’t just say that everything in society is rooted in the past. Keywords: Ideas, Principles, Philosophy, History

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    Mendeley Data
    Dataset . 2024
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    Data sources: Datacite
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    Mendeley Data
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    Data sources: Datacite
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      Mendeley Data
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      Mendeley Data
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    Authors: Bimantara, I Made Satria;

    This dataset consists of 120 Balinese story texts (as known as Satua Bali) which have been annotated for character analysis purposes, including character identification, alias clustering, and character classification into protagonist or antagonist. The labeling involved two Balinese native speakers who were fluent in understanding Balinese story texts. One of them is an expert in the fields of sociolinguistics and macrolinguistics. Reliability and level of agreement in the dataset are measured by Cohen's kappa coefficient, Jaccard similarity coefficient, and F1-score and all of them show almost perfect agreement values (>0,81). There are four main folders, each used for different character analysis purposes: 1. First Dataset (charsNamedEntity): 89,917 tokens annotated with five character named entity labels (ANM, ADJ, PNAME, GODS, OBJ) for character named entity recognition purpose 2. Second Dataset (charsExtraction): 6,634 annotated sentences for the purpose of character identification at the sentence level 3. Third Dataset (charsAliasClustering): 930 lists of character groups from 120 story texts for the purpose of alias clustering 4. Fourth Dataset (charsClassification): 848 lists of character groups that have been filtered into two groups (Protagonist and Antagonist)

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    Mendeley Data
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    Mendeley Data
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      Mendeley Data
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    Authors: Miranda, Bella;

    This is a parallel corpus dataset in which each sentence has a corresponding pair. This dataset is specifically created to facilitate the use of machine learning in the field of translation. The dataset is meticulously compiled to encompass various contexts and topics, enabling users to expand their understanding of the use of everyday language, language variations, as well as expressions and typical idioms from both languages. This dataset is independently compiled, with a total of 5261 sentences formed through the collection of online sources for the Indonesian language. Additionally, it utilizes the Malay language dictionary from the Bengkulu library, located in the city of Bengkulu, Bengkulu Province, Indonesia.

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    Mendeley Data
    Dataset . 2024
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    Mendeley Data
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    Authors: USB, Educación y Humanismo;

    Objetivo: Analizar la incidencia de la reformulación del Proyecto Ambiental Escolar (PRAE) en la educación para una ciudadanía ambiental en la escuela colombiana. Metodología: La investigación se desarrolló desde un enfoque cualitativo con la metodología de la Investigación-Acción-Participativa, teniendo como fundamento la perspectiva de Fals Borda. La población estuvo conformada por 11 estudiantes, 4 docentes, 22 padres de familia y 5 líderes comunitarios de una institución educativa. En total participaron 43 personas (21 mujeres, cifra que corresponde al 48,8% de la población estudiada, y 22 hombres, es decir el 51,2% de dicha población). Resultados:El PRAE se asume como unapolítica del discurso para el cumplimiento de la normatividad educativa, más que una acción con-sentida—apropiada por toda la comunidad académica—. Además, se establece una estrategia pedagógica de ciudadanía ambiental mediante la reformulación participativa del PRAE. Conclusiones:La reformulación colectiva fortalece los mecanismos de participación ciudadana y empoderamiento de toda la comunidad educativa para generar propuestas en su territorio desde una visión crítica; camino aún de largo aliento en muchas instituciones educativas.

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    Mendeley Data
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    Data sources: Datacite
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    Mendeley Data
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