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  • Coherence_Evaluations - cas_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - cas_environmental.csv
    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    08/10/2022
    Date Modified:
    08/10/2022
    Date Created:
    2022
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - cas_pollution.csv

    Dataset thumbnail: Coherence_Evaluations - cas_pollution.csv
    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    08/10/2022
    Date Modified:
    08/10/2022
    Date Created:
    2022
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - cas_climate.csv

    Dataset thumbnail: Coherence_Evaluations - cas_climate.csv
    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / Chicago Novel Corpus [nvl] / Newspaper Corpus [nws] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    08/10/2022
    Date Modified:
    11/11/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - cas_earth.csv

    Dataset thumbnail: Coherence_Evaluations - cas_earth.csv
    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    08/10/2022
    Date Modified:
    08/10/2022
    Date Created:
    2022
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Samvera Presentation

    Generic Work thumbnail: Samvera Presentation
    Type:
    Generic Work
    Description/Abstract:
    This is a collection of items that I used in my Samvera History Presentation.
    Creator/Author:
    Scherz, Thomas
    Submitter:
    Thomas Scherz
    Date Uploaded:
    07/12/2022
    Date Modified:
    07/12/2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Poetry Foundation Metadata

    Dataset thumbnail: Poetry Foundation Metadata
    Type:
    Dataset
    Description/Abstract:
    This file contains poet metadata for a dataset of poems collected from Poetry Foundation. This metadata relates to a poetry corpus collected from Kaggle available on that site:  https://www.kaggle.com/datasets/ultrajack/modern-renaissance-poetry Sean Ayres collected publication metadata and generated other relevant metadata fields based on his subject matter expertise. The original Kaggle poetry dataset contains approximately X lines of poetry. The metadata for this dataset references X poets
    Creator/Author:
    Ayres, Sean and McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    07/11/2022
    Date Modified:
    07/11/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Project Gutenberg Poetry Metadata

    Dataset thumbnail: Project Gutenberg Poetry Metadata
    Type:
    Dataset
    Description/Abstract:
    This file contains book metadata for a Project Gutenberg dataset of poetry metadata. This metadata relates to a poetry corpus collected by Allison Parrish available on GitHub:  https://github.com/aparrish/gutenberg-poetry-corpus Sean Ayres collected the publication metadata and generated other relevant metadata fields based on his subject matter expertise. The poetry dataset contains approximately three million lines of poetry The metadata for the dataset references X hundreds of books.
    Creator/Author:
    Ayres, Sean; McCabe, Erin E., and Parrish, Allison
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    07/11/2022
    Date Modified:
    07/11/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Monarch migration weather data, mark recapture data, and R code

    Dataset thumbnail: Monarch migration weather data, mark recapture data, and R code
    Type:
    Dataset
    Description/Abstract:
    Data and code used for the analysis of the effects of weather on the fall migration of eastern monarch butterflies.
    Creator/Author:
    Matter, Stephen F.; Guerra, Patrick ; Parlin, Adam ; Rich, Jeremy, and Taylor, Orley R.
    Submitter:
    Stephen F. Matter
    Date Uploaded:
    07/03/2022
    Date Modified:
    11/28/2022
    Date Created:
    2022
    License:
    Attribution-NonCommercial-NoDerivs 4.0 International

  • Delphi touchscreen art installation

    Media thumbnail: Delphi touchscreen art installation
    Type:
    Media
    Description/Abstract:
    Delphi - a touchscreen video game art installation for galleries and museums. Viewers can explore a contemporary interpretation of the ancient Greek site of Delphi, home of a mythical oracle. The Delphi gallery installation, designed for museums and cultural centers, gives each visitor about ten minutes to explore Delphi and visit the oracle to get a personalized message. The installation is easy to use, and accessible for general audiences of all ages and degrees of experience. Two cubes (or a cube and a chair) are placed on a 7cm high, 2m square plinth stage; the large cube is a ventilated cabinet and tabletop for a touchscreen, the other cube is a seat. As players step up onto the plinth to interact with the touchscreen to explore the virtual world, they enter the installation observed by the other gallery visitors who watch the interaction on large video screens around them, displaying the virtual environment of Delphi onto the gallery walls, with soft, ambient sound of the Greek countryside and occasional interactive events. Delphi requires controlled lighting and electricity, between 50-500 sq meters, large video displays, audio, plinth, and two cubes (or cube and chair) as above. An area of about 500 square meters is optimal, although smaller is possible. A CAVE version of Delphi is currently being researched. Visitors can explore the environment in and around the hills and monuments of Delphi. By artificial intelligence, Delphi responds by AI to each visitors style of play, actions, responses, and behavior, choosing a classic Delphic maxim (150 Delphic maxims drawn from historical and literary sources) for each player in turn. Unzip Delphi_Oracle_install.zip into a Windows folder to create a folder called Delphi_Oracle and its contents. Change directories to browse into the Delphi_Oracle folder, and double-click on Delphi_Oracle.exe to play Delphi. If Microsoft Smartscreen asks to prevent an unrecognized app, click More info, and click Run anyway. With mouse or touchscreen you can move and interact onscreen; Slow or stop, left mouse button or touch the center of the screen Move forward, mouse button or touch center top of screen (higher = faster) Move backward, mouse button or touch center bottom of screen (lower = faster) Turn right, mouse or touch right side of screen Turn left, mouse or touch left side of screen Look up and down, left and right mouse buttons together (or two fingers) A touchscreen makes it feel very immersive, and a mouse also works just fine too. Currently working to run Delphi in the CAVE software for CAVE systems. Delphi is first and foremost a work of contemporary art and an interpretive reconstruction of a cultural treasure for everyone. Looking for a contemporary art gallery where I can premiere it. -benb copyright 2022 Benjamin Britton June 14, 2022 all rights reserved
    Creator/Author:
    Britton, Benjamin
    Submitter:
    Benjamin Britton
    Date Uploaded:
    06/16/2022
    Date Modified:
    06/16/2022
    Date Created:
    2022-06-16
    License:
    All rights reserved

  • List of Problematic Plant Species and Cultivars Identified in Seven Public Gardens

    Dataset thumbnail: List of Problematic Plant Species and Cultivars Identified in Seven Public Gardens
    Type:
    Dataset
    Description/Abstract:
    Data generated from a survey of problematic plants (species and cultivars) identified in seven public gardens in the Midwestern United States and Canada. Included are: (1) List of 881 plant taxa identified as problematic in the seven different public gardens; cultivars are presented individually and not collapsed within species; (2) Collapsed list in which cultivars have been subsumed under plant species; (3) List of only cultivars identified as problematic.
    Creator/Author:
    Culley, Theresa; Havens, Kayri; Ryan, Clair; Cavallin, Nadia; Gettig, Roger; Dreisilker, Kurt; Schuler, Jessica Arcade; Landel, Hans, and Shultz, Brittany
    Submitter:
    Theresa Culley
    Date Uploaded:
    05/26/2022
    Date Modified:
    05/26/2022
    Date Created:
    May 26, 2022
    License:
    Open Data Commons Attribution License (ODC-By)