54 datasets found
  1. H

    BLIS Collective: Fabric of Repair Data & Scripts

    • dataverse.harvard.edu
    Updated May 14, 2025
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    Camilla Griffiths; Christina Pao; Trevor Smith; Savannah Romero (2025). BLIS Collective: Fabric of Repair Data & Scripts [Dataset]. http://doi.org/10.7910/DVN/B4DIVZ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 14, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Camilla Griffiths; Christina Pao; Trevor Smith; Savannah Romero
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The contained files provide data and replication code for BLIS Collective’s Fabric of Repair Report (2025): https://www.bliscollective.org/s/Fabric-of-Repair_Full-Version_LONG.pdf The data were collected by Swayable in early 2025 and analyzed internally by the BLIS Collective research team (PI: Dr. Camilla Griffiths). The data are provided as a .csv BLIS_Swayable_2025.csv and are merged from two waves of data collection.

  2. d

    Data material: Deweyan conceptualisation of habit

    • search.dataone.org
    • dataverse.no
    • +1more
    Updated Sep 25, 2024
    + more versions
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    Adalberon, Erik Yves H. (2024). Data material: Deweyan conceptualisation of habit [Dataset]. http://doi.org/10.18710/U1B7W3
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    Dataset updated
    Sep 25, 2024
    Dataset provided by
    DataverseNO
    Authors
    Adalberon, Erik Yves H.
    Description

    Collection of citations from the work of John Dewey relevant for the concept of habits. Used to generate a conceptual framework.

  3. T

    Encouraging Value Innovation by Adopting the Blue Ocean Strategy in a Batak...

    • dataverse.telkomuniversity.ac.id
    pdf
    Updated Oct 2, 2023
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    Telkom University Dataverse (2023). Encouraging Value Innovation by Adopting the Blue Ocean Strategy in a Batak Karo Fabric Business [Dataset]. http://doi.org/10.34820/FK2/NRT37F
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    pdf(470881)Available download formats
    Dataset updated
    Oct 2, 2023
    Dataset provided by
    Telkom University Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The tradition of Batak Karo fabric production has been undertaken for a long time, with many businesses in existence for multiple generations, as is the case with the trade business UD Batik Bintang HS (BBHS). Competition in this trade is extremely intense, with many companies degrading and going out of business. Innovation of new value is needed to advance businesses’ efforts to survive and thrive. In addition to the Red Ocean Strategy, in existing business arenas, the Blue Ocean Strategy (BOS) can be adopted to support such efforts. This study aimed to boost value innovation at BBHS by introducing the BOS, presenting a novel research contribution by examining a Batak Karo fabric business using a descriptive qualitative method. Interviews were used for data collection, and the credibility of the data was validated through triangulation of the data sources. Respondents included three internal employees, three customers, and three suppliers, totaling nine participants. Data analysis applied stages of reduction, display, and conclusions/verification. The discussions were engaged using the BOS constructs of strategy canvas, 4-action framework, and BOS formulation. The research results revealed two notable strategies in value innovation. First, new value innovation can be inspired by entering the supplier industry through innovation in fabric raw materials by lowering yarn density, resulting in lower consumer price without affecting quality. Second, innovation strategies included new cloth colors and motifs that dare to go beyond common customs without violating traditional standards. Both strategies represent new value innovations to attract new customers and retain existing customers. From a research perspective, this study contributes novel evidence that the BOS can be applied to broaden perspectives and identify new value innovations in traditional Batak Karo fabric businesses, with potential applicability to a broad range of traditional textile enterprises

  4. H

    Cloth Filter Data

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Mar 15, 2023
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    Onder Caliskaner; Terence K. Reid; Natalie Mastin; Tzahi Y. Cath; Amanda S. Hering (2023). Cloth Filter Data [Dataset]. http://doi.org/10.7910/DVN/NKWRCR
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Onder Caliskaner; Terence K. Reid; Natalie Mastin; Tzahi Y. Cath; Amanda S. Hering
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/NKWRCRhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/NKWRCR

    Dataset funded by
    National Science Foundation
    Description

    A list of two data frames that summarize the performance of Aqua Aerobic Systems, Inc. cloth filters for primary wastewater treatment at BC Labs. Cloth filters should treat more wastewater to a higher quality with a smaller physical footprint than a traditional primary clarifier. The first data frame contains laboratory data measuring influent and effluent water quality for both the primary cloth filter and primary clarifier. Lab samples were taken at an irregular frequency from April 6, 2017 to November 5, 2019, but samples for the cloth filter were more consistent and frequent than those taken for the primary clarifier. The second data frame contains daily operational averages of online sensor data for the primary cloth filter from January 1, 2019 to January 1, 2020, which includes process control variables. The goals were to (1) determine whether the cloth filter removes more solids and contaminants than the clarifier and (2) investigate how to improve the cloth filter performance.

  5. H

    Dataset of the paper Structural Textile Pattern Recognition and Processing...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Sep 24, 2020
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    Vuong M. Ngo (2020). Dataset of the paper Structural Textile Pattern Recognition and Processing Based on Hypergraphs [Dataset]. http://doi.org/10.7910/DVN/ZFNLES
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 24, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Vuong M. Ngo
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Dataset of textiles created from SAWU editor

  6. T

    Supplemental Material for CLOP Manuscript

    • dataverse.tdl.org
    docx, pdf, xlsx
    Updated Jun 24, 2024
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    Rowan Martindale; Rowan Martindale (2024). Supplemental Material for CLOP Manuscript [Dataset]. http://doi.org/10.18738/T8/VAE1TU
    Explore at:
    pdf(12779769), pdf(19199329), docx(34217), pdf(6768365), docx(4225020), pdf(130250), pdf(17387788), pdf(372422), pdf(422310), pdf(542391), docx(5624919), pdf(4431002), pdf(3416006), docx(27675), pdf(1502603), pdf(7576439), pdf(24991442), docx(1108364), xlsx(546135), docx(414060)Available download formats
    Dataset updated
    Jun 24, 2024
    Dataset provided by
    Texas Data Repository
    Authors
    Rowan Martindale; Rowan Martindale
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This Dataset contains the supplemental data from the manuscript: "Understanding How Entry-Level College Students Collaborate, Learn, and Engage with Geoscience Concepts when Playing Educational Games in a Lab Setting"

  7. U

    Replication data and code for analyses in R presented in: Volcanic climate...

    • dataverse.ucla.edu
    bin, html, tsv, txt
    Updated Feb 8, 2022
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    R.J. Sinensky; R.J. Sinensky (2022). Replication data and code for analyses in R presented in: Volcanic climate forcing, extreme cold and the Neolithic Transition in the northern US Southwest [Dataset]. http://doi.org/10.25346/S6/N3RVLC
    Explore at:
    tsv(92491), html(6992077), txt(42582), tsv(25713), tsv(44603), bin(28673), tsv(77600), tsv(675537), txt(3689), tsv(431249)Available download formats
    Dataset updated
    Feb 8, 2022
    Dataset provided by
    UCLA Dataverse
    Authors
    R.J. Sinensky; R.J. Sinensky
    License

    https://dataverse.ucla.edu/api/datasets/:persistentId/versions/4.3/customlicense?persistentId=doi:10.25346/S6/N3RVLChttps://dataverse.ucla.edu/api/datasets/:persistentId/versions/4.3/customlicense?persistentId=doi:10.25346/S6/N3RVLC

    Area covered
    Southwestern United States, United States
    Description

    Online Supplemental Material 2 (OSM 2) contains the data and code necessary to generate Figures 3-6, 8-9, S1 and S5-S6 presented in Sinensky et al. (2022). The R Markdown document (OSM 2.0) will render these figures using the data provided in OSM 2.1-2.6.

  8. T

    AM Material Signatures

    • dataverse.tdl.org
    xlsx
    Updated Feb 12, 2024
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    Francisco Gonzalez-Castillo; Francisco Gonzalez-Castillo (2024). AM Material Signatures [Dataset]. http://doi.org/10.18738/T8/OGHITU
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    xlsx(100189)Available download formats
    Dataset updated
    Feb 12, 2024
    Dataset provided by
    Texas Data Repository
    Authors
    Francisco Gonzalez-Castillo; Francisco Gonzalez-Castillo
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    AM Material Signature Identifiers

  9. T

    Supplementary Material to "ESG-Valued Portfolio Optimization and Dynamic...

    • dataverse.tdl.org
    pdf
    Updated Feb 10, 2025
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    W. Brent Lindquist; W. Brent Lindquist (2025). Supplementary Material to "ESG-Valued Portfolio Optimization and Dynamic Asset Pricing" [Dataset]. http://doi.org/10.18738/T8/JHH0A8
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    pdf(7605775)Available download formats
    Dataset updated
    Feb 10, 2025
    Dataset provided by
    Texas Data Repository
    Authors
    W. Brent Lindquist; W. Brent Lindquist
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset contains a single file consisting of the supplementary material for the article entitled "ESG-Valued Portfolio Optimization and Dynamic Asset Pricing". It contains nine sections. The article describes efficient frontier computations using Refinitive ESG-scores for the date 12/30/2019. Sections SM.1 compares with efficient frontier computations for the date 03/20/2020. Section SM.2 provides data tables referenced in the article. Sections SM.3 through SM.9 provides comparison results to those in the article using Robeco-SAM ESG scores.

  10. H

    Replication material for "Coalition Policy Perceptions"

    • dataverse.harvard.edu
    • search.datacite.org
    Updated Apr 21, 2019
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    Shaun Bowler; Thomas Gschwend; Indridi H. Indridason (2019). Replication material for "Coalition Policy Perceptions" [Dataset]. http://doi.org/10.7910/DVN/PLS50O
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 21, 2019
    Dataset provided by
    Harvard Dataverse
    Authors
    Shaun Bowler; Thomas Gschwend; Indridi H. Indridason
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Replication data and code in Stata

  11. d

    Data from: Reproduction Material for: Subjective Losers of Globalization

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Steiner, Nils D.; Matthias, Mader; Schoen, Harald (2023). Reproduction Material for: Subjective Losers of Globalization [Dataset]. http://doi.org/10.7910/DVN/WIHAOV
    Explore at:
    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Steiner, Nils D.; Matthias, Mader; Schoen, Harald
    Description

    These Stata files reproduce the results reported in: Steiner, Nils D./Mader, Matthias/Schoen, Harald (forthcoming): Subjective Losers of Globalization, European Journal of Political Research. The survey data sets used can be obtained directly from GESIS, see the reproduction do-file for further instructions.

  12. D

    Replication Data for: Consumer drivers for intended adoption of recycled...

    • dataverse.no
    Updated Dec 12, 2024
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    Shumaila Khatri; Shumaila Khatri; Hanne K. Sjølie; Hanne K. Sjølie; Anders Q. Nyrud; Anders Q. Nyrud (2024). Replication Data for: Consumer drivers for intended adoption of recycled wood as construction material [Dataset]. http://doi.org/10.18710/BE5TXF
    Explore at:
    text/comma-separated-values(14484), txt(5199), txt(1039), text/comma-separated-values(13872)Available download formats
    Dataset updated
    Dec 12, 2024
    Dataset provided by
    DataverseNO
    Authors
    Shumaila Khatri; Shumaila Khatri; Hanne K. Sjølie; Hanne K. Sjølie; Anders Q. Nyrud; Anders Q. Nyrud
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Norway
    Dataset funded by
    The Research Council of Norway
    Description

    The data collection was conducted to find determinants that affect adoption of recycled wood in Norway. The data was collected during 15th Dec 2023 to 5th Jan 2024 by Norstat AS via online surveys. The two datasets represent cabin-owners (count = 446) and house-owners (count = 467). All thirteen questionnaire items were marked on a Likert scale ranging from 1 (to a very small extent) to 7 (to a very large extent). Id# represents the record number for each survey-taker.

  13. S

    Supplemental material for: The dynamics of bird diversity in the new world

    • dataverse.scholarsportal.info
    • borealisdata.ca
    • +1more
    pdf +1
    Updated May 19, 2021
    + more versions
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    Scholars Portal Dataverse (2021). Supplemental material for: The dynamics of bird diversity in the new world [Dataset]. http://doi.org/10.5683/SP2/XN3FY7
    Explore at:
    pdf(3522206), text/plain;charset=utf-8(3031)Available download formats
    Dataset updated
    May 19, 2021
    Dataset provided by
    Scholars Portal Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Usage notesThe Supplementary Material includes 80 pages (Supplementary Methods and Results, 10 tables and 54 figures)

  14. N

    Supplementary Material for: Enhancing Running Exercise with IoT, Blockchain,...

    • dataverse.lib.nycu.edu.tw
    tsv
    Updated Jan 29, 2024
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    NYCU Dataverse (2024). Supplementary Material for: Enhancing Running Exercise with IoT, Blockchain, and Heart Rate Adaptive Running Music [Dataset]. http://doi.org/10.57770/KWIJHL
    Explore at:
    tsv(446)Available download formats
    Dataset updated
    Jan 29, 2024
    Dataset provided by
    NYCU Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This supplementary material comprises the anonymized raw data and grouped data of all 36 participants involved in the study. The dataset is essential for researchers seeking detailed insights into the effects of IoT, Blockchain, and Heart Rate Adaptive Running Music on running exercise. It serves as a valuable resource for further research and advanced statistical analysis. Participant Raw Data: Contains individual records for each of the 36 participants. The data is anonymized to ensure privacy and ethical compliance. Grouped Data: The participants were categorized into two distinct groups, employing a counterbalanced design. This organization facilitates easier comparative analysis and interpretation of the data.

  15. D

    Dissertation: Dealing with autonomy: Self-regulated learning in open online...

    • dataverse.nl
    • test.dataverse.nl
    docx, pdf +2
    Updated May 23, 2019
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    Renée Jansen; Renée Jansen (2019). Dissertation: Dealing with autonomy: Self-regulated learning in open online education -- Supplementary material [Dataset]. http://doi.org/10.34894/LCWRXU
    Explore at:
    docx(27297), docx(25961), docx(14920), text/x-fixed-field(23554), docx(18396), type/x-r-syntax(5319), docx(26159), docx(14584), docx(27037), pdf(229450), text/x-fixed-field(4538), type/x-r-syntax(37349), pdf(153035), text/x-fixed-field(18864), text/x-fixed-field(19504), docx(21049), docx(141632), docx(18880), docx(26526)Available download formats
    Dataset updated
    May 23, 2019
    Dataset provided by
    DataverseNL
    Authors
    Renée Jansen; Renée Jansen
    License

    https://dataverse.nl/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34894/LCWRXUhttps://dataverse.nl/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34894/LCWRXU

    Description

    Supplementary material beloning to the dissertation "Dealing with autonomy. Self-regulated learning in open online education" by Renée Jansen (Utrecht University)

  16. T

    GeoFORCE Assessment Material

    • dataverse.tdl.org
    docx, pdf
    Updated Nov 11, 2020
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    Rowan Martindale; Estefania Salgado Jauregui; Rowan Martindale; Estefania Salgado Jauregui (2020). GeoFORCE Assessment Material [Dataset]. http://doi.org/10.18738/T8/R2KSCY
    Explore at:
    pdf(1320085), pdf(2136664), pdf(1368813), docx(22888), pdf(3015331), pdf(847540), docx(18335), docx(57277), pdf(792825), pdf(809847), pdf(187908), docx(21817), pdf(3187770), pdf(3362353), pdf(4978806), pdf(220390), pdf(7796952), pdf(3058603), pdf(12537098), docx(18930)Available download formats
    Dataset updated
    Nov 11, 2020
    Dataset provided by
    Texas Data Repository
    Authors
    Rowan Martindale; Estefania Salgado Jauregui; Rowan Martindale; Estefania Salgado Jauregui
    License

    https://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/R2KSCYhttps://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/R2KSCY

    Description

    Protocols, Instructions, and Surveys used During the GeoFORCE assessment of the Taphonomy Game

  17. H

    Replication Data for: Competitive lobbying in the influence production...

    • dataverse.harvard.edu
    Updated Jan 10, 2022
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    Benjamin Egerod; Wiebke Junk (2022). Replication Data for: Competitive lobbying in the influence production process and the use of spatial econometrics in lobbying research [Dataset]. http://doi.org/10.7910/DVN/MZF8EH
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 10, 2022
    Dataset provided by
    Harvard Dataverse
    Authors
    Benjamin Egerod; Wiebke Junk
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This data package contains the material necessary for replicating the article. There are three datasets and three scripts that will replicate the results in the article. See ReadMe file for further information.

  18. T

    Supplemental Material for Martindale et al. JGE paper

    • dataverse.tdl.org
    docx, mp4, pdf, png +1
    Updated May 8, 2023
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    Rowan Martindale; Rowan Martindale (2023). Supplemental Material for Martindale et al. JGE paper [Dataset]. http://doi.org/10.18738/T8/CQMLY6
    Explore at:
    png(821167), docx(2292841), docx(27753), mp4(168422479), pdf(12533433), pdf(257295), pdf(134810), pdf(797424), docx(5624325), mp4(167514559), pdf(929430), pdf(81273), pdf(1047556), docx(37818), pdf(8247735), png(147106), docx(1786349), pdf(4407926), png(1589910), pdf(233636810), png(809844), pdf(3303340), mp4(107594560), xlsx(373127)Available download formats
    Dataset updated
    May 8, 2023
    Dataset provided by
    Texas Data Repository
    Authors
    Rowan Martindale; Rowan Martindale
    License

    https://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/CQMLY6https://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/CQMLY6

    Description

    Supplemental Material for Martindale et al. '“Reef Survivor”: A new board game designed to teach college and university undergraduate students about reef ecology, evolution, and extinction' submitted to the Journal of Geoscience Education

  19. T

    "Taphonomy: Dead and Fossilized" board game and associated educational...

    • dataverse.tdl.org
    docx, mp4, pdf
    Updated Nov 1, 2019
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    Rowan C. Martindale; Anna M. Weiss; Rowan C. Martindale; Anna M. Weiss (2019). "Taphonomy: Dead and Fossilized" board game and associated educational material tested in 2018/2019 [Dataset]. http://doi.org/10.18738/T8/UWCVKH
    Explore at:
    pdf(965272), pdf(792825), pdf(1265290), pdf(3362353), pdf(220390), pdf(187908), docx(19778), mp4(98630885), pdf(847540), pdf(1368813), pdf(239400), pdf(12537098), pdf(1320085), pdf(113077), pdf(830729), pdf(1725408), pdf(2136664), pdf(4978806), pdf(1360002), pdf(1303667), pdf(2338456), pdf(3187770), pdf(233572), pdf(3015331), pdf(7796952), pdf(2369945), pdf(3074389), pdf(1226257), pdf(3058603), pdf(809847)Available download formats
    Dataset updated
    Nov 1, 2019
    Dataset provided by
    Texas Data Repository
    Authors
    Rowan C. Martindale; Anna M. Weiss; Rowan C. Martindale; Anna M. Weiss
    License

    https://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/UWCVKHhttps://dataverse.tdl.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.18738/T8/UWCVKH

    Description

    This is the Print-and-Play version of "Taphonomy: Dead and Fossilized" that was used for testing the game's efficacy in an undergraduate classroom. This site also contains the associated educational material and instructions to play the game during the assessment.

  20. T

    Replication Data for Mahogany fruit material exploration for an essential...

    • dataverse.telkomuniversity.ac.id
    pdf
    Updated Sep 22, 2022
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    Telkom University Dataverse (2022). Replication Data for Mahogany fruit material exploration for an essential oil nebulizer in the new normal adaptation [Dataset]. http://doi.org/10.34820/FK2/5CUDMK
    Explore at:
    pdf(417792)Available download formats
    Dataset updated
    Sep 22, 2022
    Dataset provided by
    Telkom University Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This prublication is the result of material investigation strategy in product design advancement that examined the material use from Swietenia macrophylla, usually known as mahogany.

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Camilla Griffiths; Christina Pao; Trevor Smith; Savannah Romero (2025). BLIS Collective: Fabric of Repair Data & Scripts [Dataset]. http://doi.org/10.7910/DVN/B4DIVZ

BLIS Collective: Fabric of Repair Data & Scripts

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 14, 2025
Dataset provided by
Harvard Dataverse
Authors
Camilla Griffiths; Christina Pao; Trevor Smith; Savannah Romero
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Description

The contained files provide data and replication code for BLIS Collective’s Fabric of Repair Report (2025): https://www.bliscollective.org/s/Fabric-of-Repair_Full-Version_LONG.pdf The data were collected by Swayable in early 2025 and analyzed internally by the BLIS Collective research team (PI: Dr. Camilla Griffiths). The data are provided as a .csv BLIS_Swayable_2025.csv and are merged from two waves of data collection.

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