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Share, publish, and manage your data. Find and cite data across all research fields.

Welcome to the Texas Data Repository Dataverse, a research data management system for Texas Digital Library (TDL) member institutions. To add, share, and publish your data or work on a project, select your local institutional repository from the institutions below. To find datasets from across Texas institutional dataverses, start here.

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    1 to 10 of 45,660 Results
    Jan 25, 2021 - Dallas - Fort Worth
    Gao, R.S., 2021, "Model Data for Gao et al (2021) “Low pressure build-up with large disposal volumes of oilfield water: A flow model of the Ellenburger Group, Fort-Worth Basin, North-Central Texas"", https://doi.org/10.18738/T8/CEQEDF, Texas Data Repository Dataverse, V1
    This archive contains data files used in the research paper published in the AAPG Bulletin in 2021: “Low pressure build-up with large disposal volumes of oilfield water: A flow model of the Ellenburger Group, Fort-Worth Basin, North-Central Texas”. The archive contains a zip fold...
    7Z Archive - 9.7 MB - MD5: 33f781776856c1240c99ad580ab138dc
    This archive contains data files used in the research paper published in the AAPG Bulletin in 2021: “Low pressure build-up with large disposal volumes of oilfield water: A flow model of the Ellenburger Group, Fort-Worth Basin, North-Central Texas”. The archive contains a zip fol...
    Jan 20, 2021 - Texas State University Dataverse
    Bhandari, Keshav, 2021, "Egok360 A 360 Egocentric Kinetic Human Activity Video Dataset", https://doi.org/10.18738/T8/L64SHD, Texas Data Repository Dataverse, V1
    Recently, there has been a growing interest in wearable sensors which provides new research perspectives for 360 ° video analysis. However, the lack of 360 ° datasets in literature hinders the research in this field. To bridge this gap, in this paper we propose a novel Egocentric...
    Unknown - 24.7 MB - MD5: 9377dff5fd06d251b1076048ebcb0b05
    Unknown - 28.3 MB - MD5: f6ae4ca5c699963195044c2ce56dc2ad
    Unknown - 2.6 MB - MD5: 34b41e578c1478e1bb698871425e19e1
    Unknown - 8.7 MB - MD5: 332d66227f374928b2b75fe3bacf99b3
    Unknown - 6.4 MB - MD5: 6739fd39d01194e17c1bfb394cbf1475
    Unknown - 26.5 MB - MD5: 5d1053ffdeeedac6f63d1397a8ff981b
    Unknown - 28.8 MB - MD5: 71428a16b1fb3dc924e1547061958a79
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