100+ datasets found
  1. Training and Development Sets

    • kaggle.com
    zip
    Updated Feb 10, 2021
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    Avanti Shah (2021). Training and Development Sets [Dataset]. https://www.kaggle.com/avantishah/training-and-development-sets
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    zip(25201974 bytes)Available download formats
    Dataset updated
    Feb 10, 2021
    Authors
    Avanti Shah
    Description

    Dataset

    This dataset was created by Avanti Shah

    Contents

  2. d

    Business Development Company (BDC) Data Sets

    • catalog.data.gov
    Updated Sep 3, 2025
    + more versions
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    Structured Disclosure (2025). Business Development Company (BDC) Data Sets [Dataset]. https://catalog.data.gov/dataset/business-development-company-bdc-data-sets
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    Dataset updated
    Sep 3, 2025
    Dataset provided by
    Structured Disclosure
    Description

    The Business Development Company (BDC) Data Sets provide the data extracted from disclosures filed by BDCs with the Commission in eXtensible Business Reporting Language (XBRL). The data is sourced from XBRL tagged periodic reports and other disclosures submitted by BDCs to the Commission. The BDC Data Sets provide a schedule of investments report, detailed financial data sets, and a summary non-financial data set.

  3. Materials Science Named Entity Recognition: train/development/test sets

    • figshare.com
    txt
    Updated Jun 4, 2019
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    Leigh Weston (2019). Materials Science Named Entity Recognition: train/development/test sets [Dataset]. http://doi.org/10.6084/m9.figshare.8184428.v1
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    txtAvailable download formats
    Dataset updated
    Jun 4, 2019
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Leigh Weston
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Training, development and test sets for supervised named entity recognition for materials science. The data is labelled using the IOB annotation scheme. There exist 7 entity tags: material (MAT), sample descriptor (DSC), symmetry/phase label (SPL), property (PRO), application (APL), synthesis method (SMT), and characterization method (CMT), along with the outside tag (O).The data consists of 800 hand-labelled materials science abstracts. The data has an 80-10-10 split, giving 640 abstracts in the training set, 80 in the development set, and 80 in the test set.

  4. f

    Data statistics, where the number of sentences and entities are reported,...

    • datasetcatalog.nlm.nih.gov
    Updated Sep 21, 2021
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    Xie, Liang; Qian, Tao; Yan, Huijiong; Chen, Shanguang (2021). Data statistics, where the number of sentences and entities are reported, and Devel indicates the development set. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000788860
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    Dataset updated
    Sep 21, 2021
    Authors
    Xie, Liang; Qian, Tao; Yan, Huijiong; Chen, Shanguang
    Description

    Data statistics, where the number of sentences and entities are reported, and Devel indicates the development set.

  5. d

    Making Education Count for Development Data Collection and Availability in...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Mar 30, 2021
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    U.S. Department of State (2021). Making Education Count for Development Data Collection and Availability in Six PISA for Development Countries [Dataset]. https://catalog.data.gov/dataset/making-education-count-for-development-data-collection-and-availability-in-six-pisa-for-de
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    Dataset updated
    Mar 30, 2021
    Dataset provided by
    U.S. Department of State
    Description

    This report reviews the collection, availability and quality of system-level data and metadata on education from countries participating in the PISA for Development project: Cambodia, Ecuador, Guatemala, Paraguay, Senegal and Zambia. PISA for Development aims to increase low income countries’ use of PISA assessments for monitoring progress towards national goals for improving education and for analysing the factors associated with student learning outcomes, particularly among poor and marginalised populations. The project also helps track progress towards the international education targets defined in the Education 2030 Framework for Action, which the international community adopted in 2015 as the strategy for achieving the Education Sustainable Development Goal (SDG). The report suggests technically sound and viable options for improving data quality, completeness and international comparability in the six countries that are reviewed. It also provides insights into overcoming some of the challenges common to countries that participate in PISA for Development and to other middle income and low income countries.

  6. g

    XPlanung dataset BPL “Development & Supplementary Set Fornsbach-Model” |...

    • gimi9.com
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    XPlanung dataset BPL “Development & Supplementary Set Fornsbach-Model” | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_eb353fa4-0be9-44d1-8db6-f52882d1cd4a
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    License

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

    Area covered
    Fornsbach
    Description

    The development plan (BPL) contains the legally binding determinations for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Development and Supplementary Statute Fornsbach-Model” of the city of Murrhardt from XPlanung 5.0. Description: The development plan contains the legally binding determinations for the urban planning system. In principle, the development plan must be developed from the land use plan.

  7. E

    Reading Comprehension with Commonsense Reasoning Dataset (Record) -...

    • live.european-language-grid.eu
    json
    Updated Dec 30, 2018
    + more versions
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    (2018). Reading Comprehension with Commonsense Reasoning Dataset (Record) - Development set [Dataset]. https://live.european-language-grid.eu/catalogue/corpus/5145
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    jsonAvailable download formats
    Dataset updated
    Dec 30, 2018
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    https://archive.org/about/terms.phphttps://archive.org/about/terms.php

    Description

    Reading comprehension dataset which requires commonsense reasoning. Contains 120,000+ queries from 70,000+ news articles.

  8. e

    XPlanung data set BPL “Development plan three-gate line”

    • data.europa.eu
    • gimi9.com
    wfs, wms
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    XPlanung data set BPL “Development plan three-gate line” [Dataset]. https://data.europa.eu/88u/dataset/5bf41740-0337-4cfd-910a-fd6a9570645d
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    wms, wfsAvailable download formats
    Description

    The development plan (BPL) contains the legally binding determinations for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Development Plan Three-Tore-Strasse” of the city of Bühl from XPlanung 5.0. Description: Three-door road.

  9. g

    XPlanning data set BPL “Development plan downtown and adjacent sub-area”

    • gimi9.com
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    XPlanning data set BPL “Development plan downtown and adjacent sub-area” [Dataset]. https://gimi9.com/dataset/eu_c67e6604-905c-4237-8997-e91d2dd76e04/
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    License

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

    Description

    The development plan (BPL) contains the legally binding settlements for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “City Town Development Plan and adjoining Partial Flats” of the city of Gaggenau from XPlanung 5.0. Description: Urban development plan and adjacent sub-area.

  10. d

    Data from: Development Threat Index

    • catalog.data.gov
    • dataverse.harvard.edu
    • +4more
    Updated Aug 23, 2025
    + more versions
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    SEDAC (2025). Development Threat Index [Dataset]. https://catalog.data.gov/dataset/development-threat-index
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    Dataset updated
    Aug 23, 2025
    Dataset provided by
    SEDAC
    Description

    The Development Threat Index data set is a terrestrial global, future development threat map based on combining these resources: agricultural expansion, urban expansion, conventional oil and gas, unconventional oil and gas, coal, mining, biofuels, solar, and wind. Each threat ranked potential development from 0-100 with 100 indicating the highest potential for future development of the resource and were produced at a 50 square kilometer (km2) grid cell resolution, excluding all cells overlapping Antarctica and those with >50% considered marine.

  11. d

    Inspire data set BPL “Murgufer 3 development plan”. Modification; Murgufer...

    • datasets.ai
    • gimi9.com
    • +1more
    0
    Updated Mar 1, 2021
    + more versions
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    GDI-DE (2021). Inspire data set BPL “Murgufer 3 development plan”. Modification; Murgufer 5. Change» [Dataset]. https://datasets.ai/datasets/19fbf19e-8a65-40df-b52f-1c269c9c405e
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    0Available download formats
    Dataset updated
    Mar 1, 2021
    Dataset authored and provided by
    GDI-DE
    Description

    After INSPIRE transformed development plan “Murgufer 3 development plan”. Modification; Murgufer 5. Change" of the city of Gaggenau based on an XPlanung dataset in version 5.0.

  12. e

    XPlanning data set BPL “Development plan Gruenling”

    • data.europa.eu
    • gimi9.com
    wfs, wms
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    XPlanning data set BPL “Development plan Gruenling” [Dataset]. https://data.europa.eu/data/datasets/e7ae6086-7249-4167-a880-878330bf8767?locale=en
    Explore at:
    wms, wfsAvailable download formats
    Description

    The development plan (BPL) contains the legally binding settlements for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Development Plan Gruenling” of the city of Gernsbach from XPlanung 5.0. Description: Development plan Gruenling.

  13. Development Credit Authority (DCA) Data Set: Loan Transactions

    • datasets.ai
    • data.amerigeoss.org
    • +1more
    23, 40, 55, 8
    Updated Nov 28, 2021
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    US Agency for International Development (2021). Development Credit Authority (DCA) Data Set: Loan Transactions [Dataset]. https://datasets.ai/datasets/development-credit-authority-dca-data-set-loan-transactions-a8dbe
    Explore at:
    55, 8, 23, 40Available download formats
    Dataset updated
    Nov 28, 2021
    Dataset provided by
    United States Agency for International Developmenthttp://usaid.gov/
    Authors
    US Agency for International Development
    Description

    USAID's Development Credit Authority (DCA) works with investors, local financial institutions, and development organizations to design and deliver investment alternatives that unlock financing for U.S. Government priorities. USAID guarantees encourage private lenders to extend financing to underserved borrowers in new sectors and regions. This dataset is the complete list of all private loans made under USAID's DCA since it was established in 1999. To protect the personal information of borrowers and bank partners, all strategic and personal identifiable information was removed.

  14. e

    Spatial data set for local spatial development plans of the municipality of...

    • data.europa.eu
    unknown, wms
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    Spatial data set for local spatial development plans of the municipality of Płośnica [Dataset]. https://data.europa.eu/data/datasets/5c52ead4-d417-40f6-b5ce-2834c54c0400?locale=en
    Explore at:
    unknown, wmsAvailable download formats
    License

    http://inspire.ec.europa.eu/metadata-codelist/ConditionsApplyingToAccessAndUse/noConditionsApplyhttp://inspire.ec.europa.eu/metadata-codelist/ConditionsApplyingToAccessAndUse/noConditionsApply

    Description

    A set of spatial data for the local plans of the municipality of Płośnica. Register kept by the Płośnica Municipality Office on the basis of the MRPiT Regulation on spatial data sets and metadata in the field of spatial development.

  15. Z

    DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection Development Set

    • data-staging.niaid.nih.gov
    • data.niaid.nih.gov
    Updated Sep 26, 2022
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    Nolasco, Ines; Singh, Shubhr; Strandburg-Peshkin, Ariana; Gill, Lisa; Pamula, Hanna; Morford, Joe; Emmerson, Michael; Jensens, Frants; Whitehead, Helen; Kiskin, Ivan; Vidana-Villa, Ester; Lostanlen, Vincent; Morfi, Veronica; Stowell, Dan (2022). DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection Development Set [Dataset]. https://data-staging.niaid.nih.gov/resources?id=zenodo_6012309
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    Dataset updated
    Sep 26, 2022
    Dataset provided by
    La Salle, Universitat Ramon Llull
    Syracuse University
    University of Salford
    AGH University of Science and Technology,
    Biotopia, Naturkundemuseum Bayern
    University of Oxford
    University of Konstanz & Max Planck Institute of Animal Behavior
    Queen Mary University of London (QMUL)
    Tilburg University & Naturalis Biodiversity Centre
    Centre National de la Recherche Scientifique (CNRS)
    University of Surrey
    Authors
    Nolasco, Ines; Singh, Shubhr; Strandburg-Peshkin, Ariana; Gill, Lisa; Pamula, Hanna; Morford, Joe; Emmerson, Michael; Jensens, Frants; Whitehead, Helen; Kiskin, Ivan; Vidana-Villa, Ester; Lostanlen, Vincent; Morfi, Veronica; Stowell, Dan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    General Description:

    The development set for task 5 of DCASE 2022 "Few-shot Bioacoustic Event Detection" consists of 209 audio files acquired from different bioacoustic sources. The dataset is split into training and validation sets.

    Multi-class annotations are provided for the training set with positive (POS), negative (NEG) and unkwown (UNK) values for each class. UNK indicates uncertainty about a class.

    Single-class (class of interest) annotations are provided for the validation set, with events marked as positive (POS) or unkwown (UNK) provided for the class of interest.

    Folder Structure:

    Development_Set.zip

    |_Development_Set/

    |_Training_Set/
    
    
      |_JD/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_HT/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_BV/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_MT/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_WMW/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
    
    
    
    |_Validation_Set/
    
    
      |_HB/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_PB/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_ME/
    
    
        |_*.wav
    
    
        |_*.csv
    
    
      |_ML/
    
    
        |_*.wav
    
    
        |_*.csv
    

    Development_Set_AnnotationsOnly.zip has the same structure but contains only the *.csv files

    Dataset statistics

    Some statistics on this dataset are as follows, split between training and validation set and their sub-folders:

    TRAINING SET

    Number of audio recordings | 174 Total duration | 21 hours Total classes | 47

    Total events | 14229

    TRAINING SET/BV

    Number of audio recordings | 5 Total duration | 10 hours Total classes | 11 Total events | 9026 Ratio event/duration | 0.04

    Sampling rate | 24000 Hz

    TRAINING SET/HT

    Number of audio recordings | 5 Total duration | 5 hours Total classes | 5 Total events | 611 Ratio event/duration | 0.05

    Sampling rate | 6000 Hz

    TRAINING SET/JD

    Number of audio recordings | 1 Total duration | 10 mins Total classes | 1 Total events | 357 Ratio event/duration | 0.06

    Sampling rate | 22050 Hz

    TRAINING SET/MT

    Number of audio recordings | 2 Total duration | 1 hour and 10 mins Total classes | 4 Total events | 1294 Ratio event/duration | 0.04

    Sampling rate | 8000 Hz

    TRAINING SET/WMW

    Number of audio recordings | 161 Total duration | 4 hours and 40 mins Total classes | 26 Total events | 2941 Ratio event/duration | 0.24

    Sampling rate | various sampling rates

    VALIDATION SET

    Number of audio recordings | 35 Total duration | 6 hours and 17 minutes Total classes | 22

    Total events | 2007

    VALIDATION SET/HB

    Number of audio recordings | 10 Total duration | 2 hours and 38 minutes Total classes | 1 Total events | 607 Ratio event/duration | 0.7

    Sampling rate | 44100 Hz

    VALIDATION SET/PB

    Number of audio recordings | 6 Total duration | 3 hours Total classes | 2 Total events | 292 Ratio event/duration | 0.003

    Sampling rate | 44100 Hz

    VALIDATION SET/ME

    Number of audio recordings | 2 Total duration | 20 minutes Total classes | 2 Total events | 73 Ratio event/duration | 0.01

    Sampling rate | 48000 Hz

    VALIDATION SET/ML

    Number of audio recordings | 17 Total duration | 20 minutes Total classes | 17 Total events | 1035 Ratio event/duration | 0.18

    Sampling rate | 44100 Hz

    Annotation structure

    Each line of the annotation csv represents an event in the audio file. The column descriptions are as follows:

    TRAINING SET

    Audiofilename, Starttime, Endtime, CLASS_1, CLASS_2, ...CLASS_N

    VALIDATION SET

    Audiofilename, Starttime, Endtime, Q

    Classes

    DCASE2022_task5_training_set_classes.csv and DCASE2022_task5_validation_set_classes.csv provide a table with class code correspondence to class name for all classes in the Development set.

    DCASE2022_task5_training_set_classes.csv

    dataset, class_code, class_name

    DCASE2022_task5_validation_set_classes.csv

    dataset, recording, class_code, class_name

    Evaluation Set

    The Evaluation set for this task will be released on the 1st of June 2022

    Open Access:

    This dataset is available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

    Contact info:

    Please send any feedback or questions to:

    Ines Nolasco - i.dealmeidanolasco@qmul.ac.uk

  16. e

    XPlanning data set BPL “Kirchstraße – Partial development plan (origin...

    • data.europa.eu
    • gimi9.com
    wfs, wms
    Updated Apr 18, 2024
    + more versions
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    (2024). XPlanning data set BPL “Kirchstraße – Partial development plan (origin plan)” [Dataset]. https://data.europa.eu/data/datasets/e6494331-ab26-42e6-b493-ad8adee40cdb?locale=en
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    wfs, wmsAvailable download formats
    Dataset updated
    Apr 18, 2024
    Description

    The development plan (BPL) contains the legally binding settlements for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Kirchstraße – Partial Development Plan (Origin Plan)” of the Great District City of Waghäusel from XPlanung 5.0. Description: Kirchstraße, partial development plan.

  17. f

    Performance of final models for each algorithm with respect to internal...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Jan 18, 2022
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    Tam, Cao Thi; Nguyet, Nguyen Minh; Chanh, Ho Quang; Dinh The Trung; Vuong, Nguyen Lam; Sangkaew, Sorawat; Van Vinh Chau, Nguyen; Wills, Bridget; Hernandez, Bernard; Yacoub, Sophie; Holmes, Alison H.; Tuan, Nguyen Minh; Trieu, Huynh Trung; Tam, Dong Thi Hoai; Simmons, Cameron P.; Ming, Damien K.; Lam, Phung Khanh; Tien, Nguyen Thi Hanh; Georgiou, Pantelis (2022). Performance of final models for each algorithm with respect to internal 10-fold cross validation on the development set (n = 3,304). [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000302294
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    Dataset updated
    Jan 18, 2022
    Authors
    Tam, Cao Thi; Nguyet, Nguyen Minh; Chanh, Ho Quang; Dinh The Trung; Vuong, Nguyen Lam; Sangkaew, Sorawat; Van Vinh Chau, Nguyen; Wills, Bridget; Hernandez, Bernard; Yacoub, Sophie; Holmes, Alison H.; Tuan, Nguyen Minh; Trieu, Huynh Trung; Tam, Dong Thi Hoai; Simmons, Cameron P.; Ming, Damien K.; Lam, Phung Khanh; Tien, Nguyen Thi Hanh; Georgiou, Pantelis
    Description

    The 95% confidence intervals shown in brackets were derived from bootstrap resampling of the development and testing against out of bag samples, repeated 1,000 times.

  18. e

    XPlanning data set BPL “Semi-development plan Halberg”

    • data.europa.eu
    • gimi9.com
    wfs, wms
    Updated Dec 30, 2020
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    (2020). XPlanning data set BPL “Semi-development plan Halberg” [Dataset]. https://data.europa.eu/data/datasets/f7648f56-63e2-4b1f-937e-bf8d805aa460?locale=en
    Explore at:
    wms, wfsAvailable download formats
    Dataset updated
    Dec 30, 2020
    Description

    The development plan (BPL) contains the legally binding settlements for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Halfberg Partial Development Plan” of the town of Niedernhall from XPlanung 5.0. Description: Sub-development plan Halberg; Construction line plan; Usage: WA.

  19. e

    XPlanning data set BPL “Long road (project and development plan)”

    • data.europa.eu
    wfs, wms
    + more versions
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    XPlanning data set BPL “Long road (project and development plan)” [Dataset]. https://data.europa.eu/data/datasets/f3404776-282b-4439-ac7e-9f6efd9efc3b?locale=en
    Explore at:
    wfs, wmsAvailable download formats
    Description

    The development plan (BPL) contains the legally binding settlements for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Lange Straße (project and development plan)” of the municipality of Affalterbach from XPlanung 5.0. Description: Long road (project and development plan).

  20. e

    XPlanung data set BPL “Development plan Kelterplatz”

    • data.europa.eu
    • gimi9.com
    wfs, wms
    + more versions
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    XPlanung data set BPL “Development plan Kelterplatz” [Dataset]. https://data.europa.eu/data/datasets/1a55772d-4bbb-4cb6-b708-a937550a80b8?locale=en
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    wms, wfsAvailable download formats
    Description

    The development plan (BPL) contains the legally binding determinations for the urban planning order. In principle, the development plan must be developed from the land use plan. The available data is the development plan “Development Plan Kelterplatz” of the town of Gernsbach from XPlanung 5.0. Description: Development plan Kelterplatz.

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Avanti Shah (2021). Training and Development Sets [Dataset]. https://www.kaggle.com/avantishah/training-and-development-sets
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Training and Development Sets

Explore at:
zip(25201974 bytes)Available download formats
Dataset updated
Feb 10, 2021
Authors
Avanti Shah
Description

Dataset

This dataset was created by Avanti Shah

Contents

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