cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.qeseup
title: Occurrence Download

description: A dataset containing 200 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-98.25938 19.38501,-98.26417 19.3618,-98.27216 19.20513,-97.99175 19.19715,-98.00946 19.38619,-98.25938 19.38619,-98.25938 19.38501))",
 "TaxonKey is Pinales"
 ]
}

 The dataset includes 200 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024707-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7hza7m
title: Occurrence Download

description: A dataset containing 49754 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Schoenoplectus tabernaemontani (C.C.Gmel.) Palla"
 ]
}

 The dataset includes 49754 records from 418 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024704-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr03807.v2
title: National Health Interview Survey, 1994: Second Longitudinal Study on Aging, Wave 3, 2000
title: Version 2

description: The Second Longitudinal Study of Aging (LSOA II) is a
collaborative effort of the National Center for Health Statistics
(NCHS) and the National Institute on Aging (NIA). The NATIONAL HEALTH
INTERVIEW SURVEY, 1994: SECOND SUPPLEMENT ON AGING (SOA II) (ICPSR
2563) serves as the baseline for this study. LSOA II, Wave 3 consists
of 7,936 survivor interviews and 906 decedent interviews in two data
files: the Survivor File (Part 1) and the Decedent File (Part 2). The
Survivor File contains one record for each sample person (N = 9,447)
interviewed at baseline and includes information drawn from several
additional sources, including the 1994 National Health Interview
Survey (ICPSR 6724) core questionnaire, the 1994 National Health
Interview Survey: Family Resources Supplement (ICPSR 2656), Phase I of
the 1994 National Health Interview Survey on Disability (ICPSR 2539),
and the SOA II baseline interview (ICPSR 2563). Wave 3 questions
(beginning at variable SF3664) examined migration, convalescent home
utilization, nutrition, influenza immunization, mammogram, prostate,
and cholesterol screenings, routine use of vitamins, aspirin, calcium
supplements, and antioxidants, and detailed questions on home health
care utilization. In addition, a random one-quarter sample of the
follow-up respondents were chosen to complete the Childhood Health and
Family Longevity Module. This section is similar to that administered
during the 1996 Health and Retirement Survey (HRS). Variable SF3462
indicates whether the sample person answered the childhood module. For
the Decedent File (Part 2), information was gathered from a family
member or close relative regarding sample persons (N = 906) who were
deceased at the time of Wave 3 interviews. Questions focused on
housing, long-term care, assistance with key activities, chronic
conditions, cognitive functioning, health care use, and health
insurance.
description: All individuals 70 years of age and over, for whom data
 were collected as part of the 1994 National Health Interview Survey
 core interview. The NHIS core interview used a stratified multistage
probability design.
description: Datasets: 
DS0: Study-Level Files
DS1: Survivor Data File
DS2: Decedent Data File
description: Civilian, noninstitutionalized population of the 50 states
and the District of Columbia.
description: Per agreement with NCHS, ICPSR distributes the
data files and technical documentation in this collection in their
original form as prepared by NCHS.
DOI: 10.15468/dl.s872q4
title: Occurrence Download

description: A dataset containing 126904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Natural History Museum (London) Collection Specimens",
 "TaxonKey is Aves",
 "Year is less than or equal to 3000"
 ]
}

 The dataset includes 126904 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009334-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ut5j3
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Suillus discolor (A.H.Sm., Thiers & O.K.Mill.) N.H.Nguyen"
 ]
}

 The dataset includes 22 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001699-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ke5xyv
title: Occurrence Download

description: A dataset containing 429 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cavoliniidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 429 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001701-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28270949
title: Data dictionary - bodyweight of dogs, cats, rabbits, and guinea pigs

description: Calculation of standard bodyweights for dogs, cats, rabbits, and guinea pigsStuart D. Becker, Dan G. O’Neill, Siân-Marie Frosini, Laura E. Stapleton, David M. Hughes, Dave C. BrodbeltPlos One (2025) doi: 10.1371/journal.pone.0318734This item is the data dictionary for data sets used to calculate standard bodyweights adjusted for juvenile growth in dogs, cats, rabbits, and guinea pigs. Please see linked paper for methodology.
DOI: 10.15468/dl.yxc7zw
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Dipodascopsis tothii (Zsolt) L.R.Batra & Millner"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001702-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28270892
title: GuineaPig - bodyweights 2014-23

description: Calculation of standard bodyweights for dogs, cats, rabbits, and guinea pigsStuart D. Becker, Dan G. O’Neill, Siân-Marie Frosini, Laura E. Stapleton, David M. Hughes, Dave C. BrodbeltPlos One (2025) doi: 10.1371/journal.pone.0318734This item is the data set used to calculate standard bodyweights adjusted for juvenile growth in guinea pigs. Please see linked paper for methodology.
DOI: 10.5281/zenodo.14814719
title: Copilot's responces, March and April 2024

description: The dataset consists of copy-pasted Copilot's responces to 10 pre-designed prompts. They were collected on 28 March and 4 April 2024. The prompts were inputted in three iterations. The answers from all three iterations are displayed in the document.
DOI: 10.5281/zenodo.14814720
title: Copilot's responces, March and April 2024

description: The dataset consists of copy-pasted Copilot's responces to 10 pre-designed prompts. They were collected on 28 March and 4 April 2024. The prompts were inputted in three iterations. The answers from all three iterations are displayed in the document.
DOI: 10.15468/dl.uydkqc
title: Occurrence Download

description: A dataset containing 2838 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "TaxonKey is Phocoena phocoena (Linnaeus, 1758)"
 ]
}

 The dataset includes 2838 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001703-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cvhdyc
title: Occurrence Download

description: A dataset containing 345 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Limacinidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 345 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001704-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11474285
title: Understandability in Java Decompilation

description: Data and tools of the paper "Demystifying and Assessing Code Understandability in Java Decompilation".

Data

Our data in the directory `data/` includes two directories `data/original` and `data/testset`, representing the original data set and the test set. Both directories include three parts:1. Experimental data including source code and corresponding code decompiled by CFR, Fernflower and Jadx respectively in directory `code`.2. Calculation results in directory `results`.3. The annotated dataset `relative_understandability_<original/testset>.csv` denotes the relative understandability of the file decompiled by the decompiler compared to the original file, in which -1, indicating that the decompiled file is less understandable than the original file; 0, signifying equivalent; and 1, indicating more understandable.

Tools

Our tools in the directory `tool/` includes tools for assessing the understandability of decompiled code with perplexity, Cognitive Complexity and Cognitive Complexity for Decompilation.

Environment

- System: Ubuntu 20.04- Python: python 3.10  pip install kenlm  pip install javalang- Java: JDK >= 11

Perplexity Calculator

`perplexity_calculator.py` calculates the perplexity of n-gram models for a Java file.`5-gram.binary` is our 5-gram language model.

python perplexity_calculator.py <5-gram.binary> <file>

Where <5-gram.binary> represents path to the n-gram model, <file> represents the Java file to be evaluated.

Cognitive Complexity Calculator and Cognitive Complexity for Decompilation Calculator

`CognitiveComplexityCalculator-1.0.jar` calculates the Cognitive Complexity for Java files.`CognitiveComplexityforDecompilationCalculator-1.1.jar` calculates the Cognitive Complexity for Decompilation for Java files.

java -jar CognitiveComplexityCalculator-1.0.jar <input_directory> <output_file>java -jar CognitiveComplexityforDecCalculator-1.1.jar <input_directory> <output_file>

Where <input_directory> represents the directory of all Java files to analyze, including all the files in the subdirectories. <output_file> represents where the output file is created.

The output file is a .csv file which contains the Cognitive Complexity or Cognitive Complexity for Decompilation value for each method. Specifically it contains:

- Absolute Module Path: The path of the class containing the method- Module Position: The line in the .java file where the method starts- Module declaration: The method signature and return type or pattern type- Max Nesting: The maximum level of nesting reached by the method (considering as 1 the starting level)- Cognitive Complexity or Cognitive Complexity for Decompilation

Reference



Cognitive Complexity Calculator: https://github.com/BruhZul/cognitive-complexity-calculator

MetricsReloaded: https://github.com/BasLeijdekkers/MetricsReloaded/

DepDigger: A Tool for Detecting Complex Low-Level Dependencies: https://www.sosy-lab.org/~dbeyer/DepDigger/
DOI: 10.5281/zenodo.11474286
title: Understandability in Decompilation

description: Data and tools of the paper "Demystifying and Assessing Code Understandability in Java Decompilation".

Data

Our data in the directory `data/` includes two directories `data/original` and `data/testset`, representing the original data set and the test set. Both directories include three parts:1. Experimental data including source code and corresponding code decompiled by CFR, Fernflower and Jadx respectively in directory `code`.2. Calculation results in directory `results`.3. The annotated dataset `relative_understandability_<original/testset>.csv` denotes the relative understandability of the file decompiled by the decompiler compared to the original file, in which -1, indicating that the decompiled file is less understandable than the original file; 0, signifying equivalent; and 1, indicating more understandable.

Tools

Our tools in the directory `tool/` includes tools for assessing the understandability of decompiled code with perplexity, Cognitive Complexity and Cognitive Complexity for Decompilation.

Environment

- System: Ubuntu 20.04- Python: python 3.10  pip install kenlm  pip install javalang- Java: JDK >= 11

Perplexity Calculator

`perplexity_calculator.py` calculates the perplexity of n-gram models for a Java file.`5-gram.binary` is our 5-gram language model.

python perplexity_calculator.py <5-gram.binary> <file>

Where <5-gram.binary> represents path to the n-gram model, <file> represents the Java file to be evaluated.

Cognitive Complexity Calculator and Cognitive Complexity for Decompilation Calculator

`CognitiveComplexityCalculator-1.0.jar` calculates the Cognitive Complexity for Java files.`CognitiveComplexityforDecompilationCalculator-1.0.jar` calculates the Cognitive Complexity for Decompilation for Java files.

java -jar CognitiveComplexityCalculator-1.0.jar <input_directory> <output_file>java -jar CognitiveComplexityforDecCalculator-1.0.jar <input_directory> <output_file>

Where <input_directory> represents the directory of all Java files to analyze, including all the files in the subdirectories. <output_file> represents where the output file is created.

The output file is a .csv file which contains the Cognitive Complexity or Cognitive Complexity for Decompilation value for each method. Specifically it contains:

- Absolute Module Path: The path of the class containing the method- Module Position: The line in the .java file where the method starts- Module declaration: The method signature and return type or pattern type- Max Nesting: The maximum level of nesting reached by the method (considering as 1 the starting level)- Cognitive Complexity or Cognitive Complexity for Decompilation

Reference

1. Cognitive Complexity Calculator: https://github.com/BruhZul/cognitive-complexity-calculator
DOI: 10.5281/zenodo.14869917
title: Understandability in Java Decompilation

description: Data and tools of the paper "Demystifying and Assessing Code Understandability in Java Decompilation".

Data

Our data in the directory `data/` includes two directories `data/original` and `data/testset`, representing the original data set and the test set. Both directories include three parts:1. Experimental data including source code and corresponding code decompiled by CFR, Fernflower and Jadx respectively in directory `code`.2. Calculation results in directory `results`.3. The annotated dataset `relative_understandability_<original/testset>.csv` denotes the relative understandability of the file decompiled by the decompiler compared to the original file, in which -1, indicating that the decompiled file is less understandable than the original file; 0, signifying equivalent; and 1, indicating more understandable.

Tools

Our tools in the directory `tool/` includes tools for assessing the understandability of decompiled code with perplexity, Cognitive Complexity and Cognitive Complexity for Decompilation.

Environment

- System: Ubuntu 20.04- Python: python 3.10  pip install kenlm  pip install javalang- Java: JDK >= 11

Perplexity Calculator

`perplexity_calculator.py` calculates the perplexity of n-gram models for a Java file.`5-gram.binary` is our 5-gram language model.

python perplexity_calculator.py <5-gram.binary> <file>

Where <5-gram.binary> represents path to the n-gram model, <file> represents the Java file to be evaluated.

Cognitive Complexity Calculator and Cognitive Complexity for Decompilation Calculator

`CognitiveComplexityCalculator-1.0.jar` calculates the Cognitive Complexity for Java files.`CognitiveComplexityforDecompilationCalculator-1.1.jar` calculates the Cognitive Complexity for Decompilation for Java files.

java -jar CognitiveComplexityCalculator-1.0.jar <input_directory> <output_file>java -jar CognitiveComplexityforDecCalculator-1.1.jar <input_directory> <output_file>

Where <input_directory> represents the directory of all Java files to analyze, including all the files in the subdirectories. <output_file> represents where the output file is created.

The output file is a .csv file which contains the Cognitive Complexity or Cognitive Complexity for Decompilation value for each method. Specifically it contains:

- Absolute Module Path: The path of the class containing the method- Module Position: The line in the .java file where the method starts- Module declaration: The method signature and return type or pattern type- Max Nesting: The maximum level of nesting reached by the method (considering as 1 the starting level)- Cognitive Complexity or Cognitive Complexity for Decompilation

Reference



Cognitive Complexity Calculator: https://github.com/BruhZul/cognitive-complexity-calculator

MetricsReloaded: https://github.com/BasLeijdekkers/MetricsReloaded/

DepDigger: A Tool for Detecting Complex Low-Level Dependencies: https://www.sosy-lab.org/~dbeyer/DepDigger/
DOI: 10.15468/dl.gdaf93
title: Occurrence Download

description: A dataset containing 131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Citrullus mucosospermus (Fursa) Fursa"
 ]
}

 The dataset includes 131 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001705-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kbcfed
title: Occurrence Download

description: A dataset containing 1047 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Populus euphratica Olivier"
 ]
}

 The dataset includes 1047 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000000-250214090457908/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14869990
title: Dataset for Fractionation and mechanism of Fe in the mineral-associated soil fraction from the Mongolian Plateau grasslands
DOI: 10.5281/zenodo.14869991
title: Dataset for Fractionation and mechanism of Fe in the mineral-associated soil fraction from the Mongolian Plateau grasslands
DOI: 10.5281/zenodo.10977560
title: Locityper loci database, 1KGP genotypes and benchmarking data
DOI: 10.5281/zenodo.12607584
title: Locityper loci database, 1KGP genotypes and benchmarking data
DOI: 10.5281/zenodo.14861498
title: Locityper loci database, 1KGP genotypes and benchmarking data
DOI: 10.5281/zenodo.14869751
title: Copilot's responses, January 2025

description: The dataset includes 50 pre-designed prompts and responces provided by the chatbot Copilot. The prompts were inputted on 16- 17 January 2025. The orange boxes display the prompts. The Copilot's responces are provided below the orange boxes. All the responces were directly copied/pasted from the chat.
DOI: 10.5281/zenodo.14869752
title: Copilot's responses, January 2025

description: The dataset includes 50 pre-designed prompts and responces provided by the chatbot Copilot. The prompts were inputted on 16- 17 January 2025. The orange boxes display the prompts. The Copilot's responces are provided below the orange boxes. All the responces were directly copied/pasted from the chat.
DOI: 10.15468/dl.ddkued
title: Occurrence Download

description: A dataset containing 143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Clionaidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 143 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000001-250214090457908/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jyxdsn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Colletotrichum paranaense C.A.D.Bragança & Damm"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000002-250214090457908/datasets/export for details.
DOI: 10.21227/an8a-zh27
title: Raw WiFi CSI File

description: This comes from four scenario environments (including lab, conference room, classroom, and office), Three WiFi router devices with different models and number of antennas, including Xiaomi mini, Fixom K2P, and PulianWR886N, were used to collect raw WiFi CSI files in AP mode using CSI TOOL through an Intel 5300 IWL wireless network card. A WiFi device is fixed in the scene, a subject is walking in the room, and an attacker is listening and collecting CSI data outside the room. The CSI acquisition data is 100Hz, and the data is collected 25 times continuously at 5 second intervals, including two states of someone and no one in the room.
DOI: 10.25592/uhhfdm.11675
title: Lessons on Mandinka Orthography (NCAC_RDD_TAPE_0375A)

description: Mandinka orthography
description: Published by NCAC - National Digital Archive of The Gambia, initiated by University of Hamburg, Asia-Africa-Institute, Germany, funded by Gerda Henkel Foundation, Germany
DOI: 10.25592/uhhfdm.11674
title: Lessons on Mandinka Orthography (NCAC_RDD_TAPE_0375A)

description: Mandinka orthography
description: Published by NCAC - National Digital Archive of The Gambia, initiated by University of Hamburg, Asia-Africa-Institute, Germany, funded by Gerda Henkel Foundation, Germany
DOI: 10.6084/m9.figshare.28270883
title: Dog - bodyweights 2014-23

description: Calculation of standard bodyweights for dogs, cats, rabbits, and guinea pigsStuart D. Becker, Dan G. O’Neill, Siân-Marie Frosini, Laura E. Stapleton, David M. Hughes, Dave C. BrodbeltPlos One (2025) doi: 10.1371/journal.pone.0318734This item is the data set used to calculate standard bodyweights adjusted for juvenile growth in dogs. Please see linked paper for methodology.<br>
DOI: 10.6084/m9.figshare.28270886
title: Cat - bodyweights 2014-23

description: Calculation of standard bodyweights for dogs, cats, rabbits, and guinea pigsStuart D. Becker, Dan G. O’Neill, Siân-Marie Frosini, Laura E. Stapleton, David M. Hughes, Dave C. BrodbeltPlos One (2025) doi: 10.1371/journal.pone.0318734This item is the data set used to calculate standard bodyweights adjusted for juvenile growth in cats. Please see linked paper for methodology.
DOI: 10.6084/m9.figshare.28270889
title: Rabbit - bodyweights 2014-23

description: Calculation of standard bodyweights for dogs, cats, rabbits, and guinea pigsStuart D. Becker, Dan G. O’Neill, Siân-Marie Frosini, Laura E. Stapleton, David M. Hughes, Dave C. BrodbeltPlos One (2025) doi: 10.1371/journal.pone.0318734This item is the data set used to calculate standard bodyweights adjusted for juvenile growth in rabbits. Please see linked paper for methodology.