cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10266973
title: Hardknott Roman Fort guard tower

description: One of the most remote and dramatically sited Roman forts in Britain, the small, three-acre fort at Hardknott (Cumbria, UK) enjoyed command of the Eskdale Valley and the Roman road to Ravenglass. The fort was established early in the second century AD.

This is the eastern of four internal guard towers located at the corners of the fort, which have no entrances at ground level.

https://www.english-heritage.org.uk/visit/places/hardknott-roman-fort/history/

The model was created from 126 photographs.

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10266976
title: Dirleton Headstone

description: Headstone in Dirleton Parish Kirk Churchyard, East Lothian

99 photographs using Huawei Mate Pro 10 mobile

Source: Objaverse 1.0 / Sketchfab
DOI: 10.5281/zenodo.10266975
title: Dirleton Headstone

description: Headstone in Dirleton Parish Kirk Churchyard, East Lothian

99 photographs using Huawei Mate Pro 10 mobile

Source: Objaverse 1.0 / Sketchfab
DOI: 10.25439/rmt.21944840.v1
title: Australian public lending library locations (2016-2018)

description: An historical database of libraries around Australia based on official sources for each state compiled in 2016 by Carl Higgs for analysis in the Creating Liveable Cities report [1], and updated in 2018 using then available data for use in the Australian National Liveability Study [2]. Where data were not publicly available, or recent (at that time), contact was made to request the data. The CSV file contains harmonised data including coordinates in WGS84 EPSG 4326 and features the following fields (only with values where applicable and present in the source data or other-wise derived such as coordinates via geocoding, or added for metadata documentation of data source): ID,Library,Address,Suburb,State,Postcode,Type,Holdings,latitude,longitude,year,geocode notes,Catchment,source_publisher,source_url,source_description,source_licence,source_retrieval_date. Data sources and details are described in metadata.yml <br> [1]: Arundel J, Lowe M, Hooper P, Roberts R, Rozek J, Higgs C, Giles-Corti B. Creating liveable cities in Australia: Mapping urban policy implementation and evidence-based national liveability indicators2017 5 January 2018. Available from: https://apo.org.au/node/113921. [2]: Higgs C, Rozek J, Roberts R, Both A, Arundel J, Lowe M, Hooper P, Villanueva K, Simons K, Mavoa S, Gunn L, Badland H, Davern M, Giles-Corti B. The Australian National Liveability Study 2018 datasets: spatial urban liveability indicators for 21 cities. Healthy Liveable Cities Lab, RMIT University, figshare, https://doi.org/10.25439/rmt.15001230 (2022).
DOI: 10.25439/rmt.21944840
title: Australian public lending library locations (2016-2018)

description: An historical database of libraries around Australia based on official sources for each state compiled in 2016 by Carl Higgs for analysis in the Creating Liveable Cities report [1], and updated in 2018 using then available data for use in the Australian National Liveability Study [2]. Where data were not publicly available, or recent (at that time), contact was made to request the data. The CSV file contains harmonised data including coordinates in WGS84 EPSG 4326 and features the following fields (only with values where applicable and present in the source data or other-wise derived such as coordinates via geocoding, or added for metadata documentation of data source): ID,Library,Address,Suburb,State,Postcode,Type,Holdings,latitude,longitude,year,geocode notes,Catchment,source_publisher,source_url,source_description,source_licence,source_retrieval_date. Data sources and details are described in metadata.yml <br> [1]: Arundel J, Lowe M, Hooper P, Roberts R, Rozek J, Higgs C, Giles-Corti B. Creating liveable cities in Australia: Mapping urban policy implementation and evidence-based national liveability indicators2017 5 January 2018. Available from: https://apo.org.au/node/113921. [2]: Higgs C, Rozek J, Roberts R, Both A, Arundel J, Lowe M, Hooper P, Villanueva K, Simons K, Mavoa S, Gunn L, Badland H, Davern M, Giles-Corti B. The Australian National Liveability Study 2018 datasets: spatial urban liveability indicators for 21 cities. Healthy Liveable Cities Lab, RMIT University, figshare, https://doi.org/10.25439/rmt.15001230 (2022).
DOI: 10.5517/ccdc.csd.cc2d6773
title: CCDC 2210524: Experimental Crystal Structure Determination

description: Related Article: Xinkun Ren, Bo M. Couture, Ningyu Liu, Manjinder S. Lall, Jeffrey T. Kohrt, Rudi Fasan|2022|J.Am.Chem.Soc.|145|537|doi:10.1021/jacs.2c10775
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d6xdy
title: CCDC 2211180: Experimental Crystal Structure Determination

description: Related Article: Guillermo Marcos-Ayuso, Marconi N. Peñas-Defrutos, Ana M. Gallego, Max García-Melchor, Jesús M. Martínez-Ilarduya, Pablo Espinet|2022|J.Am.Chem.Soc.|145|527|doi:10.1021/jacs.2c10842
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d7s3k
title: CCDC 2212008: Experimental Crystal Structure Determination

description: Related Article: Fanji Kong, Pablo Ríos, Conner Hauck, Francisco José Fernández-de-Córdova, Diane A. Dickie, Laurel G. Habgood, Amor Rodríguez, T. Brent Gunnoe|2022|J.Am.Chem.Soc.|145|179|doi:10.1021/jacs.2c09471
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21937613.v1
title: GGCMI phase2 inputs and outputs

description: GGCMI phase2 climate inputs and outputs of corn and soybean in the US Midwest.
DOI: 10.34740/kaggle/dsv/4891365
title: AutoXGB
DOI: 10.6084/m9.figshare.21756548
title: Supplementary Material for: Association between Carbonic Anhydrase VI (CA VI) gene copy number and dental caries experience

description: The current study examined the association between the carbonic anhydrase VI (CA VI) copy number variations (CNVs) and dental caries experience in adults. In total, 202 of 35-72 years old subjects participating in the Lithuanian National Oral Health Survey (LNOHS) agreed to provide saliva samples, thus their data were included in the current study. Information about sociodemographic, environmental, and behavioural determinants was acquired via the self-administered World Health Organisation (WHO) questionnaire. Fluoride levels in the drinking water were recorded based on information provided by water suppliers. Dental caries experience was recorded by one calibrated examiner using the WHO criteria for recording caries on smooth (including proximal, buccal, and oral) or occlusal surfaces. Caries experience was measured as the total number of decayed (D3), missing (M), filled (F) surfaces (D3MFS). DNA was extracted from saliva samples to examine CA VI CNVs using the QX200 droplet digital PCR system. Negative binomial regression and Poisson regression analyses were employed for data analyses. Based on multivariable regression analyses, higher copy number of CA VI were associated with higher caries experience on smooth surfaces (IRR 1.04, 95% CI 1.005 – 1.08) and occlusal surfaces (IRR 1.02, 95% CI 1.003 – 1.04). Positive associations between higher copy number of CA VI and higher caries experience on smooth and occlusal surfaces were found, suggesting that the CA VI coding gene may be associated with caries development. Future studies are needed to validate our results and to examine the underlying mechanisms of such associations.
DOI: 10.34740/kaggle/dsv/4891387
title: Elon Musk Tweets
DOI: 10.5281/zenodo.7559989
title: Literature review of occurrence and transmission dynamics of SARS-CoV2 in mammal animals

description: A literature review has been conducted, focusing on susceptibility of wild and domestic animal species reported under field and laboratory conditions, considering different diagnostic tests (e.g., virus isolation, RNA and antibody detection), infection dynamic, pathogenesis, immunity and further transmission of the virus. Review protocol and data extraction tables are available. The following review questions were considered: Which mammal species have been reported positive to SARS CoV 2 in the field (either at RNA, isolated virus, antibodies), and their geographical distribution? Which wild and domestic mammal species are susceptible to SARS CoV 2 in laboratory conditions <em>Dynamic of infection and pathogenesis</em>: What are confirmed infection routes for these species? What is the length of the incubation period in these species What are the clinical signs, if any, their severity, duration, etc. Which species are able to shed the virus (even in absence of clinical signs) Do these species develop protective immunity Which of these species can further transmit the disease to same/other species ? What are the genetic virus variants in each species where it is isolated? In which animals vaccines against SARS CoV 2 have been tested, and what are the results in terms of immunogenicity, protection to challenge, or safety? Which diagnostic tests are used in animals to detect SARS CoV Type of test Test performance (Se, Sp) Sample matrix used
description: EU; xlsx; docx; biohaw@efsa.europa.eu
DOI: 10.5281/zenodo.7559990
title: Literature review of occurrence and transmission dynamics of SARS-CoV2 in mammal animals

description: A literature review has been conducted, focusing on susceptibility of wild and domestic animal species reported under field and laboratory conditions, considering different diagnostic tests (e.g., virus isolation, RNA and antibody detection), infection dynamic, pathogenesis, immunity and further transmission of the virus. Review protocol and data extraction tables are available. The following review questions were considered: Which mammal species have been reported positive to SARS CoV 2 in the field (either at RNA, isolated virus, antibodies), and their geographical distribution? Which wild and domestic mammal species are susceptible to SARS CoV 2 in laboratory conditions <em>Dynamic of infection and pathogenesis</em>: What are confirmed infection routes for these species? What is the length of the incubation period in these species What are the clinical signs, if any, their severity, duration, etc. Which species are able to shed the virus (even in absence of clinical signs) Do these species develop protective immunity Which of these species can further transmit the disease to same/other species ? What are the genetic virus variants in each species where it is isolated? In which animals vaccines against SARS CoV 2 have been tested, and what are the results in terms of immunogenicity, protection to challenge, or safety? Which diagnostic tests are used in animals to detect SARS CoV Type of test Test performance (Se, Sp) Sample matrix used
description: EU; xlsx; docx; biohaw@efsa.europa.eu
DOI: 10.5281/zenodo.7563554
title: PERTEMUAN 5_26 JANUARY 2023_PTKP DAN PPh TERUTANG_UNIVERSITAS WIJAYA PUTRA_PRIGEN

description: Capaian Pembelajaran Mata Kuliah (CPMK) <strong>Mahasiswa</strong><strong> </strong><strong>mampu</strong><strong> </strong><strong>menjelaskan</strong><strong> </strong><strong>dan</strong><strong> </strong><strong>menghitung</strong><strong>: </strong><strong>Penghasilan</strong><strong> </strong><strong>Tidak</strong><strong> </strong><strong>kena</strong><strong> </strong><strong>pajak</strong><strong> (PTKP), </strong><strong>PPh</strong><strong> </strong><strong>Terhutang</strong> <strong>Indikator</strong><strong> </strong><strong>Pembelajaran</strong> <strong>Penghasilan</strong><strong> </strong><strong>Tidak</strong><strong> </strong><strong>Kena</strong><strong> </strong><strong>Pajak</strong><strong> (PTKP)</strong> 1.Besarnya PTKP; 2.Hal-hal Yang mempengaruhi <strong>Penghitungan</strong><strong> </strong><strong>PPh</strong><strong> </strong><strong>Terhutang</strong> 1.Tarif PPh Orang Pribadi; 2.Tarif PPh Badan; 3.Fasilitas Pengurangan Tarif (Pasal 31 E UU PPh).
description: PERTEMUAN 5_26 JANUARY 2023_PTKP DAN PPh TERUTANG_UNIVERSITAS WIJAYA PUTRA_PRIGEN
DOI: 10.5281/zenodo.7563553
title: PERTEMUAN 5_26 JANUARY 2023_PTKP DAN PPh TERUTANG_UNIVERSITAS WIJAYA PUTRA_PRIGEN

description: Capaian Pembelajaran Mata Kuliah (CPMK) <strong>Mahasiswa</strong><strong> </strong><strong>mampu</strong><strong> </strong><strong>menjelaskan</strong><strong> </strong><strong>dan</strong><strong> </strong><strong>menghitung</strong><strong>: </strong><strong>Penghasilan</strong><strong> </strong><strong>Tidak</strong><strong> </strong><strong>kena</strong><strong> </strong><strong>pajak</strong><strong> (PTKP), </strong><strong>PPh</strong><strong> </strong><strong>Terhutang</strong> <strong>Indikator</strong><strong> </strong><strong>Pembelajaran</strong> <strong>Penghasilan</strong><strong> </strong><strong>Tidak</strong><strong> </strong><strong>Kena</strong><strong> </strong><strong>Pajak</strong><strong> (PTKP)</strong> 1.Besarnya PTKP; 2.Hal-hal Yang mempengaruhi <strong>Penghitungan</strong><strong> </strong><strong>PPh</strong><strong> </strong><strong>Terhutang</strong> 1.Tarif PPh Orang Pribadi; 2.Tarif PPh Badan; 3.Fasilitas Pengurangan Tarif (Pasal 31 E UU PPh).
description: PERTEMUAN 5_26 JANUARY 2023_PTKP DAN PPh TERUTANG_UNIVERSITAS WIJAYA PUTRA_PRIGEN
DOI: 10.5281/zenodo.5777315
title: Talking Trucks

description: Talking Trucks dataset (v2021.12) This dataset is used for research into Self-organizing logistics and published as part of the paper "Talking Trucks: Decentralized Collaborative Multi-Agent Order Scheduling for Self-Organizing Logistics". It is managed by the TNO Sustainable Transport and Logistics department. Please contact Christian van Ommeren (christian.vanommeren@tno.nl) and Ruben Fransen (ruben.fransen@tno.nl) for details. The dataset contains 4 types of objects (files): agents, orders, route stops, and locations; and currently holds data for three experiments, represented by a UUIDv4 identifier. <strong>Agents</strong> Represents an agent that is able to transport load and is to be assigned to specific orders. This file contains the agent's unique UUIDv4 identifier; agent type; Euronorm emission norm; agent cost for driving a km in EUR; agent cost per hour in EUR; working hours start and end times; and agent starting coordinates. <strong>Orders</strong> Represents the unit that should be transported by the agents. This file contains the order's unique UUIDv4 identifier; container type; TEU; trade type (import/export); and weight. <strong>Route stops</strong> Represents the stop which is associated with an order. Stops are tied to a real-world location. This file contains the route stop's unique UUIDv4 identifier; stop index; location UUIDv4 identifier; type (origin/destination); order UUIDv4 identifier; and time window times. <strong>Locations</strong> Represents a real-world location at which logistics operations take place (for a specific duration). This file contains the location's unique UUIDv4 identifier; country designator; coordinates; Euronorm emission norm; stop duration; and service type (decoupling, live handling, craning, ...). <strong>License</strong> This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
DOI: 10.5281/zenodo.5777314
title: Talking Trucks

description: Talking Trucks dataset (v2021.12) This dataset is used for research into Self-organizing logistics and published as part of the paper "Talking Trucks: Decentralized Collaborative Multi-Agent Order Scheduling for Self-Organizing Logistics". It is managed by the TNO Sustainable Transport and Logistics department. Please contact Christian van Ommeren (christian.vanommeren@tno.nl) and Ruben Fransen (ruben.fransen@tno.nl) for details. The dataset contains 4 types of objects (files): agents, orders, route stops, and locations; and currently holds data for three experiments, represented by a UUIDv4 identifier. <strong>Agents</strong> Represents an agent that is able to transport load and is to be assigned to specific orders. This file contains the agent's unique UUIDv4 identifier; agent type; Euronorm emission norm; agent cost for driving a km in EUR; agent cost per hour in EUR; working hours start and end times; and agent starting coordinates. <strong>Orders</strong> Represents the unit that should be transported by the agents. This file contains the order's unique UUIDv4 identifier; container type; TEU; trade type (import/export); and weight. <strong>Route stops</strong> Represents the stop which is associated with an order. Stops are tied to a real-world location. This file contains the route stop's unique UUIDv4 identifier; stop index; location UUIDv4 identifier; type (origin/destination); order UUIDv4 identifier; and time window times. <strong>Locations</strong> Represents a real-world location at which logistics operations take place (for a specific duration). This file contains the location's unique UUIDv4 identifier; country designator; coordinates; Euronorm emission norm; stop duration; and service type (decoupling, live handling, craning, ...). <strong>License</strong> This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
DOI: 10.25502/835j-rj35/d
title: Data diallel analysis of soybean for root and dry matter traits

description: Additional data generated from the PhD thesis research.
DOI: 10.6084/m9.figshare.21946421
title: Raw_acceleration_data.xlsx

description: The file contains raw data for acceleration analysis in a paper entitled ' Field Testing of Railway Embankment Dynamics During Train Passage.'
DOI: 10.3217/gvzyw-1ea97
title: Linear Uncertainty Propagation in Multiline TRL Calibration: Dataset and Code

description: Wave parameter measurements of a coplanar waveguide (CPW) multiline thru-reflect-line calibration kit on an Alumina substrate.
DOI: 10.17632/vry9nmtg8g.1
title: Purpose in Life. Raw (per-item) Data. 2019

description: The raw (per-item) data collected via administering the Purpose-In-Life Test. For every participant, her code and obtained results are provided. Purpose-In-Life Test was developed by J.C. Crumbaugh and L.T. Maholick (1976). The Russian adaptation was made by D.A. Leontiev (1988). It consists of 20 statements that should be rated using a 7-point Likert type scale.
DOI: 10.17632/ycy9zmhts5.1
title: Biomedical data and sensing information in smart rooms

description: This is a new dataset, including behavioral, biometric, and environmental data, obtained from 23 subjects each spending 1 week to 2 months in smart rooms in Tokyo, Japan. The approximate duration of the experiment is 2 years. This dataset includes personal data, such as the use of home appliances, heartbeat rate, sleep status, temperature, and illumination. Although there are many datasets that publish these data individually, datasets that publish them all at once, tied to individual IDs, are valuable. The number of days for which data were obtained was 488, the number of records was 18,418,359, and the total size of the obtained data was 2.76 GB. This dataset can be used for machine learning and analysis for tips on getting a good night's sleep, for example.
DOI: 10.5441/002/edbt.2017.80
title: Multi-model Data Management: What's New and What's Next?
DOI: 10.17632/5f4rfjjh3d.1
title: Posttraumatic Growth. Raw (per-item) Data. 2019

description: The raw (per-item) data collected by administering the Posttraumatic Growth Inventory. For each participant, her code and individual results are represented. Posttraumatic Growth Inventory was developed by R.G. Tedeschi and L.G. Calhoun (1996). The Russian adaptation was made by M.Sh. Magomed-Eminov (2004). It consists of 21 items and includes the following subscales: Relating to others, New Possibilities, Personal Strength, Spiritual Change, and Appreciation of Life. Each item should be rated on a 6-point Likert type scale where (0) – no changes happened; (1) – a very small degree of changes; (2) – a small degree; (3) – a moderate degree; (4) – a great degree; (5) – a very great degree of changes.
DOI: 10.5281/zenodo.1411211
title: Fantom5 Transcribed Enhancers In Mm10

description: <strong>Overview</strong>

Transcribed enhancers were identified and their expression was quantified across all human FANTOM5 libraries, following the re-aligned FANTOM5 CAGE data upon mm10 (GRCm38) (obtained from http://fantom.gsc.riken.jp/5/datafiles/reprocessed/mm10_v1/basic/), and decomposition-based peak identification (obtained from https://zenodo.org/record/545682#.WPuNy1Pyv2Q) by Kawaji, Hideya.

<strong>Description</strong>

Transcribed enhancers were called based on bidirectional balanced RNA signatures as per Andersson et al (2014). Enhancers were only identified distal to known exons (+/-100bp region from boundaries) and transcription start sites (+/-300bp), defined by GENCODE vM7 annotation. In total, 44,138 enhancers were identified across 1,068 libraries and the expression was quantified. For details regarding the identification of transcribed enhancers from CAGE data, please see Andersson et al (2014) and blog post.

Due to varying noise levels across FANTOM5 libraries and the intrinsic low expression levels of transcribed enhancers, library-specific noise levels were estimated to define of robust set of enhancers in each sample. In summary, for each library, expression was quantified in randomly sampled genomic regions distal to assembly gaps, DNase hypersensitive sites (ENCODE), known exons and gene TSSs (GENCODE vM7) to create a genomic background expression distribution. For each library, we called an enhancer active (used) if its expression was above the 99.9th quantile of the library’s genomic background expression distribution. The robust set of enhancers consist of those significantly expressed in at least one library.

While this approach ensures less permissive enhancer calling in noisy libraries, for some libraries the noise threshold is zero meaning that a single CAGE tag is sufficient for calling an enhancer active. Furthermore, the possibility of detecting enhancer transcription is affected by sequencing depth, so the number of active enhancers per library might not be biologically meaningful to compare when sequencing depths differ.

<strong>Data files</strong><br>
Each predicted enhancer is described in BED12 format with two blocks denoting the merged regions of transcription initiation on the minus and plus strands. The thickStart and thickEnd columns denote the inferred mid position between blocks of transcription initiation events. Expression and usage matrices are tab delimited and the first row gives the FANTOM5 CNhs IDs and the first column the enhancer ID (same as column 4 in BED file). Usage matrices contain zeroes and ones (0:not used, 1:used).


	enhancers (BED12 format)
	enhancer expression matrix (tab delimited, first row: CNhs IDs, first column: enhancer ID (coordinate))
	binary enhancer usage matrix (0:not used, 1:used, tab delimited, first row: CNhs IDs, first column: enhancer ID (coordinate))