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Code for "Formally Comparing Topic Models and Human-Generated Qualitative Coding of Physician Mothers' Experiences of Workplace Discrimination" This repository contains the code used in "Formally Comparing Topic Models and Human-Generated Qualitative Coding of Physician Mothers' Experiences of Workplace Discrimination" by Adam S. Miner, Sheridan A. Stewart, Meghan C. Halley, Laura K. Nelson, and Eleni Linos. Please refer to the original paper in Big Data & Society. In this paper, we evaluate whether topic models identify themes similar to those found by human coders in a prior qualitative analysis of physician mothers' experiences of workplace discrimination. More detail is available at the main page for the repository.

Full Changelog: https://github.com/maehr/the-corpus-as-a-network/commits/v0.1.0-alpha If you use this dataset, please cite it using the metadata from this file.

gCube Catalogue (gCat) API is a library containing classes shared across gcat* components. gCube is an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments, such as the D4Science Infrastructure, by favouring the realisation of reuse-oriented policies. gCube has been used to successfully build and operate infrastructures and virtual research environments for application domains ranging from biodiversity to environmental data management and cultural heritage. gCube offers components supporting typical data management workflows including data access, curation, processing, and visualisation on a large set of data typologies ranging from primary biodiversity data to geospatial and tabular data. D4Science is a Hybrid Data Infrastructure combining over 500 software components and integrating data from more than 50 different data providers into a coherent and managed system of hardware, software, and data resources. The D4Science infrastructure drastically reduces the cost of ownership, maintenance, and operation thanks to the exploitation of gCube. The source code of this software version is available at: https://code-repo.d4science.org/gCubeSystem/gcat-api/releases/tag/v2.3.0

gCube Catalogue (gCat) Service allows any client to publish on the gCube Catalogue. gCube is an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments, such as the D4Science Infrastructure, by favouring the realisation of reuse-oriented policies. gCube has been used to successfully build and operate infrastructures and virtual research environments for application domains ranging from biodiversity to environmental data management and cultural heritage. gCube offers components supporting typical data management workflows including data access, curation, processing, and visualisation on a large set of data typologies ranging from primary biodiversity data to geospatial and tabular data. D4Science is a Hybrid Data Infrastructure combining over 500 software components and integrating data from more than 50 different data providers into a coherent and managed system of hardware, software, and data resources. The D4Science infrastructure drastically reduces the cost of ownership, maintenance, and operation thanks to the exploitation of gCube. The source code of this software version is available at: https://code-repo.d4science.org/gCubeSystem/gcat/releases/tag/v2.4.1

gCube Catalogue (gCat) Client is a library designed to interact with REST API exposed by the gCat Service. gCube is an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments, such as the D4Science Infrastructure, by favouring the realisation of reuse-oriented policies. gCube has been used to successfully build and operate infrastructures and virtual research environments for application domains ranging from biodiversity to environmental data management and cultural heritage. gCube offers components supporting typical data management workflows including data access, curation, processing, and visualisation on a large set of data typologies ranging from primary biodiversity data to geospatial and tabular data. D4Science is a Hybrid Data Infrastructure combining over 500 software components and integrating data from more than 50 different data providers into a coherent and managed system of hardware, software, and data resources. The D4Science infrastructure drastically reduces the cost of ownership, maintenance, and operation thanks to the exploitation of gCube. The source code of this software version is available at: https://code-repo.d4science.org/gCubeSystem/gcat-client/releases/tag/v2.0.0

Code for the IDSEM dataset, first version. IDSEM is an acronym for "an Invoices Database of the Spanish Electricity Market" This database contains electricity bills related to energy consumption in Spanish households. The contents of bills are automatically generated using this code. The main purpose of the dataset is for training machine learning algorithms, especially for designing new methods for extracting information from invoices. There are 86 different labels, which are related to several topics, such as the customer and marketer, the contract, energy consumption, or billing. The code relies on a set of dictionaries and template documents for generating many training and test samples. The file format of invoices is PDF and the labels are stored in JSON files. More information can be found at https://idsem.ulpgc.es/ and in the following article: [1] Javier Sánchez, Agustín Salgado, Alejandro García, and Nelson Monzón, "IDSEM, an invoices database of the Spanish electricity market", Sci. Data, (2022). Full Changelog: https://github.com/jsanchezperez/idsem/commits/v1.0.0

R package for an easy way to draw chronological charts from tables, aiming to include an intuitive environment for anyone new to R. Includes 'ggplot2' geoms and theme for chronological charts. {"references": ["Thomas Rose and Chiara Girotto (2022). chronochrt: Creating Chronological Charts with R. R package version 0.1.2. https://CRAN.R-project.org/package=chronochrt"]} Changes to version 0.1.1 * Update to maintain compatibility with newer versions of packages ChronochRt depends on. * import_chron() now has default arguments for the column names.

A hosted version of this notebook is available on Google Colaboratory. It requires no coding to use. If downloaded, this notebook must be run in Google Colab! Link: darcmode.org/scraper The Disboard Scraper and Analysis Notebook is a research toolkit for Internet scholars interested in examining networks of Discord servers. It includes tools for collecting and analyzing data from Disboard.org. This is a Google Colaboratory version of the Modified Disboard Scraper, a fork of DisboardScraper by DiscordFederation. It is written in Python and Markdown. The Disboard Scraper and Analysis Notebook is maintained by the Discord Academic Research Community, a collective of Internet scholars interested in Discord research. {"references": ["Heslep, D. G., & Berge, P. (2021). Mapping Discord's darkside: Distributed hate networks on Disboard. New Media & Society, 14614448211062548. https://doi.org/10.1177/14614448211062548"]}

Current version: v1.0.0 Tools and examples for working with GLAM information in Wikidata. For more information see the Wikidata section of the GLAM Workbench. Notebook topics Create a Gannt chart of Australian government departments – visualises life dates of government departments Create a network graph visualisation of Australian government departments – visualises changes in Australian government departments over time Visualise the connections of a single Australian government agency See the GLAM Workbench for more details.

With our game „Excavation Manager 2022“ we want to show the steps and difficulties of an archaeological excavation. The player takes on the role of the excavation director and selects a level at the beginning. There are currently two levels to choose from: An excavation in south-eastern Turkey, in the remains of the ancient city of Doliche (medium difficulty) and one in the city centre of Osnabrück, in mediaeval layers (hard difficulty). Both campaigns are based on actual excavation projects, and many of the finds that the player can make really come from there. But it is not an exact replica of the real models and the player can also find things that were not made in the real world - or in the worst case nothing at all. However, before the excavation cuts can be made, an application for funding must always be submitted first. If the funding application is accepted, these funds must then be carefully spent on staff and tools. This preparation of the excavation takes place in several menus, while the campaign itself in the field is shown in a top-down-view and the player controls the excavation director as a movable avatar. The chance of success depends on these decisions just as much as the subsequent placement of the cuts and the careful uncovering of the finds in the field. Finally, the player receives a high score against which he can measure his success. We would like to thank the Research Centre Asia Minor of the WWU Münster (especially Michael Blömer) and the City Archaeology of Osnabrück (especially Judith Franzen) for providing numerous photos of original finds for our game! Thank you xDeviruchi for creating free 8-bit music and adding an acoustical layer to the Excavation Manager 2022! Check them out here: https://xdeviruchi.itch.io/ Made with Unity GitHub: https://github.com/flhel/Excavation-Manager-2022 More information on the accompanying university website. {"references": ["https://github.com/flhel/Excavation-Manager-2022"]}