cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/nd64mvxtym.1
title: Real-Life OR Scheduling Data at UZGent (Mar-Aug 2021)

description: This dataset addresses a specific issue in operating room scheduling, integrating the surgical case planning problem with the short-term surgeon scheduling problem within a one-to-two-week planning horizon. The problem is inspired by real-life situations at Ghent University Hospital (UZGent) in Belgium. The main objective is to efficiently sequence surgeons across different rooms and days, planning their surgical lists to maximize the daily priority attained.

The dataset consists of two parts:

Instances: This part represents real-life environments and includes a case study conducted at UZGent. To gather the necessary instance information, we conducted interviews with key personnel responsible for composing OR schedules and examined the OR logbook from March 2021. This resulted in the collection of data for 24 instances, with each instance representing the activities of a single week. The total number of patients ranges from 50 to 80 for medium-sized instances (e.g., G00) and 100 to 160 for large-sized instances (e.g., G01). Additionally, this part includes higher-level data in the MSS (Master Surgery Schedule) folder for each instance group.

BCnP: This part contains the final solutions reported by the proposed Branch-Cut-and-Price (BCnP) algorithm. BCnP is divided into two subfolders, each containing 24 solutions in XML format, indicated by ["Ins_"]+[instance number][...].XML.

The findings of this research are detailed in our recent study titled "A dedicated branch-price-and-cut algorithm for surgical case planning and surgeon scheduling," which is currently awaiting peer review. Further information, including the DOI, will be provided upon acceptance.

The information regarding the MSS is already described in our study:
Akbarzadeh, B., & Maenhout, B. (2024). A study on policy decisions to embed flexibility for reactive recovery in the planning and scheduling process in operating rooms. Omega, 103061.

Notes:
All files are in HTML format, organized in an object-oriented manner using related tag objects.
Each file starts with a "description" tag that provides a preview of its contents.
DOI: 10.17632/wtm6sygnmg.3
title: Single Cell Atlas of the Adult Drosophila Ovary

description: Data for Rust, et al., 2019
DOI: 10.17632/h357t5dv6k.1
title: Concrete training images

description: This data set contains three different size training data of concrete crack
DOI: 10.17632/t3fh4jzpx4.1
title: Survival Data in Prostate Cancer

description: Prostate cancer data from SEER.
DOI: 10.17632/f6fcsy9hnx.1
title: Abis Lines Mutual Fund Strategy Descriptions
DOI: 10.15468/dl.3mn4n7
title: Occurrence Download

description: A dataset containing 1362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (United States of America, Mexico, Guatemala, Belize, El Salvador, Honduras, Nicaragua, Costa Rica, Panama)",
 "OccurrenceStatus is Present",
 "TaxonKey is Lomaridium C.Presl"
 ]
}

 The dataset includes 1362 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009169-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6yrdmwydzj.1
title: Supplement for "Delgocitinib ointment in pediatric patients with atopic dermatitis: a phase 3, randomized, double-blind, vehicle-controlled study and a subsequent open-label, long-term study"

description: Supplementary Information and Results - Nakagawa H, et al. Delgocitinib ointment in pediatric patients with atopic dermatitis: a phase 3, randomized, double-blind, vehicle-controlled study and a subsequent open-label, long-term study.
DOI: 10.17632/vxkgg72db8.1
title: CRL dataset

description: database for correlation of crl at first trimester and lga fetuses
DOI: 10.17632/bkgk8nrxjs.1
title: Iron in Northeast India: Antiquity and Functional Uses

description: The data collected shows the literature available on iron especially in the case of northeast India. Historically, the impact of iron propelled the society towards progress likewise, in the case of mainland India this aspect has been discussed and debated by many scholars and is still generating a vibrant exchange of opinions amongst scholars from different disciplines. However, in the case of northeast India is not privileged enough in this case. Hence, my quest was to trace the antiquity of iron in the region to further the debates surrounding iron in northeast India as well. Therefore, from this, I was able to gather information on the antiquity of iron and the various sources of iron in the region.
DOI: 10.17632/p8rv84hrbs.1
title: Thalassemia Dataset

description: About Dataset

- Researchers Information 
Safa S. Abdul-Jabbar1, Alaa k. Farhan 2
1Computer Science Dept., College of Science for Women, University of Baghdad, Baghdad, Iraq
2Computer Science Dept., University of Technology, Baghdad, Iraq
1safa.s@csw.uobaghdad.edu.iq ,2 Alaa.K.Farhan@uotechnology.edu.iq

- Context
This is the first Dataset for various thalassemia patients in Iraq. The Dataset contains the HLPC test information for 1073 patients with 12 features for each record that can be used to create a thalassemia Diagnosis system. Also, this Data was collected in 2022 from Hematology Center (Thalassemia) in Ibn Al-Baladi Hospital and can be analyzed using any programming language because it is provided in an excel file that can be accessed and manipulated easily. 
- Content
This Dataset contains 1073 rows. For each row (patient HLPC information), there are 12 columns containing test features that can be described as follows:
1.	ID: Patients Identifier
2.	Gender: Patient sex (0 for Female and 1 for Male)
3.	Age: Patient's age in years
4.	MCV: Mean Corpuscular Volume with Normal Ranges 82.5 98 for adults.
5.	HGB: Hemoglobin with Normal Ranges: (for Males 13.6 - 16.9, Females 11.9 - 14.8) Grams per deciliter.
6.	MCH: Mean Corpuscular Hemoglobin is the average amount of hemoglobin in the average red cell with Normal Ranges (27 – 32) picograms for adults
7.	RBC: Red Blood Cell with Normal Ranges: (for Males 4.2 - 5.7, Females 3.8 - 5.0) 10^6/microliter.
8.	S: Subunits of HLPC Test with Normal Range =0%. 
9.	HBA2: Subunits of HLPC Test with Normal Range (1-3) % for adults
10.	HBA: Subunits of HLPC Test with Normal Range (> 97) % for adults
11.	HBF: Subunits of HLPC Test with Normal Range (<1) % for adults
12.	Iron: Iron in Blood cells with Normal Range (60 – 170) micrograms per deciliter 

- Acknowledgements
We thank the entire Ibn Al-Baladi Hospital / Hematology Center team, especially the director of the Hematology Center in Ibn Al-Baladi Hospital, for cooperating with us in collecting this data while maintaining patients' confidentiality.
DOI: 10.17632/yyhzy94bym.2
title: Joireman et al. (JBR, Pandemic Fee Paper) - Data (Studies 1-3)

description: Note: This data is from Joireman, Karabas, & Munaganti's (JBR, conditionally accepted) paper titled: Customer Backlash against Pandemic Surcharges: The Mediating Role of Inferred Negative Motives and Implications for the “Surcharge Economy”. 

Abstract: The services sector was adversely affected by the pandemic. Supply chain disruptions, staff shortages, and low customer traffic led revenues to decline. To offset these challenges, some businesses introduced pandemic surcharges, which were not well received by customers. The current work aimed to understand customer backlash against pandemic surcharges and test potential strategies to reduce negative reactions to such surcharges. Across three experiments, results offer evidence for a key mediator whereby surcharges increase perceived negative firm motives, which leads to lower purchase, return, and tipping intentions. Making the surcharge optional and justifying it based on lost business were ineffective in reducing negative response to the surcharge. However, explaining that the surcharge was needed to cover additional cleaning costs or buy safety equipment reduced inferred negative motives and consequently increased purchase and tipping intentions. Implications for a broader “surcharge economy” are discussed.
DOI: 10.17632/tzrjx692jy.1
title: Synthetic Dataset for PII Detection and Anonymization in Financial Documents

description: This dataset is designed for Training and Testing Machine Learning Models for Detecting and Anonymizing Personally Identifiable Information (PII) in financial documents. This dataset adheres to the highest data privacy standards and is fully synthetic, ensuring no real-world personal data is included. The dataset simulates various PII entities typically found in financial contexts. It is intended to support the development and evaluation of PII Detection and Anonymization Models. It includes training and testing sets of Synthetic Entries generated using realistic financial document structures.

Each entry simulates real-world financial texts such as auditor reports, tax filings, compliance notices, and transaction confirmations. The dataset contains a variety of Synthetic PII types embedded into these documents, including:

• Names
• Social Security Numbers (SSNs)
• Credit Card Numbers
• Phone Numbers
• Email Addresses
• Physical Addresses
• Company Names
• URLs

Dataset Structure:

The Training and Testing Datasets have the following structure of Synthetic Data:

Columns:

1. Name: Contains the synthetic full names of individuals, generated with a mix of genders and cultural backgrounds.

2. Credit Card: Lists synthetic credit card information, including card numbers, expiration dates, and security codes. Various credit card types (e.g., VISA, MasterCard, American Express) are represented.

3. Email: Includes synthetic email addresses in realistic formats with diverse domain names.

4. URL: Contains synthetic website URLs from various domains (e.g., .com, .org, .info), mimicking the variety found in real financial documents.

5. Phone: Represents synthetic phone numbers in different formats, including international formats.

6. Address: Consists of detailed synthetic addresses, including street names, cities, states, and postal codes, generated in various formats.

7. Company: Includes synthetic company names across different industries, providing a realistic mix of common and unique names.

8. SSN: Synthetic Social Security Numbers (SSNs) presented in various formats, including different region-specific patterns (e.g., with or without hyphens).

9. Text: The main body of text simulating financial document content such as audits, reports, invoices, compliance notices, or transaction confirmations. Each text entry contains embedded PII data.

10. True Predictions: Lists and Annotates the exact starting and ending character positions of each PII entity within the "Text" column, along with the entity type (e.g., 'name', 'email', 'address', etc.).

Please Note: This dataset does not contain any real-world Sensitive Information.
DOI: 10.15468/dl.ga36yx
title: Occurrence Download

description: A dataset containing 498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Picea jezoensis (Siebold & Zucc.) Carrière",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 498 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009170-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.swpatm
title: Occurrence Download

description: A dataset containing 128364 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Xerces Society - Bumble Bee Watch"
 ]
}

 The dataset includes 128364 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020549-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14986317
title: CMIP6 input data usage information for IPCC WGI AR6 figure 10.20

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 10.20 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 10.20.
DOI: 10.5281/zenodo.14986777
title: Ultralow Velocity Zones at the Core-Mantle Boundary Near the Caroline Hotspot

description: This dataset consists 2070 pairs of BHE and BHN waveform data.
DOI: 10.5281/zenodo.14986778
title: Ultralow Velocity Zones at the Core-Mantle Boundary Near the Caroline Hotspot

description: This dataset consists 2070 pairs of BHE and BHN waveform data.
DOI: 10.26050/wdcc/ar6.c6spcsaes585
title: IPCC DDC: CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 ScenarioMIP ssp585

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CSIRO.ACCESS-ESM1-5.ssp585' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6spgigegs585
title: IPCC DDC: NASA-GISS GISS-E2.1G model output prepared for CMIP6 ScenarioMIP ssp585

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.NASA-GISS.GISS-E2-1-G.ssp585' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The GISS-E2.1G climate model, released in 2019, includes the following components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
DOI: 10.26050/wdcc/ar6.c6spinic8s245
title: IPCC DDC: INM INM-CM4-8 model output prepared for CMIP6 ScenarioMIP ssp245

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.INM.INM-CM4-8.ssp245' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM4-8 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.