cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24586371.v1
title: Microarray profile of HaCaT cells

description: miRVana, miR-1290 mimic, and control (Thermo Fisher Scientific) were transfected into HaCaT cells in using Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA, USA). Each RNA sample was assessed using a microarray (SurePrint G3 Human Gene Expression 8 × 60 K Microarray; Agilent Technologies, Palo Alto, CA, USA), and the expression profiles were analyzed using GeneSpring software (v12; Agilent Technologies).
DOI: 10.6084/m9.figshare.24580708
title: Microarray analysis of miRNA expression

description: We analyzed serum miRNA levels (total of 2,565 miRNAs) in patients with PsA at baseline (n = 3), patients with PsA post-granulocyte and monocyte adsorption apheresis (n = 3), and healthy controls (n = 3) using microarray sequencing. Total RNA, including miRNAs, was isolated from sera using the miRNeasy Serum/Plasma kit and miRNeasy Mini kit (QIAGEN Japan, Tokyo, Japan) according to the manufacturers’ instructions. Spike-in controls were used as serum samples. The miRNAs were analyzed using the 3D-Gene miRNA Oligo chip (Toray, Tokyo, Japan).
DOI: 10.5281/zenodo.10155811
title: diseasome

description: Overview
This is a dataset of diseases and the genes associated with them. In this dataset, a disease is a node and a gene is a hyperedge. The "label" attribute of the nodes gives the disease description and the "label" attribute of the edges gives the gene name. The disease-disease correlations were filtered out to enforce only disease-gene relationships.
Statistics
Some basic statistics of this dataset are:

number of nodes: 516
number of hyperedges: 903
The dataset is connected
Source of original data
Source: Gephi
References
If you use this dataset, please cite these references:

The human disease network. Kwang-Il Goh, Michael E. Cusick, David Valle, and Albert-László Barabási. Proceedings of the National Academy of Sciences (PNAS), 2007.
DOI: 10.5281/zenodo.10155812
title: diseasome

description: Overview
This is a dataset of diseases and the genes associated with them. In this dataset, a disease is a node and a gene is a hyperedge. The "label" attribute of the nodes gives the disease description and the "label" attribute of the edges gives the gene name. The disease-disease correlations were filtered out to enforce only disease-gene relationships.
Statistics
Some basic statistics of this dataset are:

number of nodes: 516
number of hyperedges: 903
The dataset is connected
Source of original data
Source: Gephi
References
If you use this dataset, please cite these references:

The human disease network. Kwang-Il Goh, Michael E. Cusick, David Valle, and Albert-László Barabási. Proceedings of the National Academy of Sciences (PNAS), 2007.
DOI: 10.5281/zenodo.10155822
title: email-EU

description: Overview
This hypergraph dataset was generated using email data from a large European research institution for a period from October 2003 to May 2005 (18 months). Information about all incoming and outgoing emails between members of the research institution has been anonymized. The e-mails only represent communication between institution members (the core), and the dataset does not contain incoming messages from or outgoing messages to the rest of the world.
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. Timestamps are in ISO8601 format. In email communication, messages can be sent to multiple recipients. In this dataset, nodes are email addresses at a European research institution. The original data source only contains directed temporal edge tuples (sender, receiver, timestamp), where timestamps are recorded at 1-second resolution. The hyperedges are undirected and consist of a sender and all receivers grouped such that the email between the sender and each receiver has the same timestamp.
Statistics
Some basic statistics of this dataset are:

number of nodes: 1,005
number of timestamped hyperedges: 235,263
distribution of the connected components:
Component Size, Number 

986, 1
1, 19
Source of original data
Source: email-Eu dataset
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction, Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
Local Higher-order Graph Clustering, Hao Yin, Austin R. Benson, Jure Leskovec, and David F. Gleich. Proceedings of KDD, 2017.
Graph Evolution: Densification and Shrinking Diameters, Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. ACM Transactions on Knowledge Discovery from Data, 2007.
DOI: 10.5281/zenodo.10155823
title: email-EU

description: Overview
This hypergraph dataset was generated using email data from a large European research institution for a period from October 2003 to May 2005 (18 months). Information about all incoming and outgoing emails between members of the research institution has been anonymized. The e-mails only represent communication between institution members (the core), and the dataset does not contain incoming messages from or outgoing messages to the rest of the world.
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. Timestamps are in ISO8601 format. In email communication, messages can be sent to multiple recipients. In this dataset, nodes are email addresses at a European research institution. The original data source only contains directed temporal edge tuples (sender, receiver, timestamp), where timestamps are recorded at 1-second resolution. The hyperedges are undirected and consist of a sender and all receivers grouped such that the email between the sender and each receiver has the same timestamp.
Statistics
Some basic statistics of this dataset are:

number of nodes: 1,005
number of timestamped hyperedges: 235,263
distribution of the connected components:
Component Size, Number 

986, 1
1, 19
Source of original data
Source: email-Eu dataset
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction, Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
Local Higher-order Graph Clustering, Hao Yin, Austin R. Benson, Jure Leskovec, and David F. Gleich. Proceedings of KDD, 2017.
Graph Evolution: Densification and Shrinking Diameters, Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. ACM Transactions on Knowledge Discovery from Data, 2007.
DOI: 10.6084/m9.figshare.19145432
title: Online learning experiences of social work students in India.sav

description: This is a dataset on the online learning experience of 202 social work students from India, collected in 2022. The full article associated with this dataset can be found at- https://www.researchgate.net/publication/374820796_Online_learning_experiences_of_social_work_students_in_India
DOI: 10.6084/m9.figshare.19145432.v1
title: Online learning experience of social work students in India.sav

description: This is a dataset on the online learning experience of 202 social work students from India, collected in 2022.
DOI: 10.6084/m9.figshare.19335098.v3
title: <b>Wellbeing of Palliative Care Workers During Covid-19 Pandemic: Implications for Social Work Practice</b>

description: This is a dataset on the wellbeing of 114 palliative care workers from India during the covid-19 pandemic. The full article associated with this dataset can be found at https://www.researchgate.net/publication/362836867_Wellbeing_of_Palliative_Care_Workers_During_Covid-19_Pandemic_Implications_for_Social_Work_Practice
DOI: 10.5281/zenodo.10155835
title: tags-ask-ubuntu

description: Overview
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In this dataset, nodes are tags, and hyperedges are the sets of tags applied to questions on askubuntu.com. The timestamps are in ISO8601 format and are normalized to start at 0. This dataset is derived from tags on Ask Ubuntu posts.
Statistics
Some basic statistics of this dataset are:

number of nodes: 3,029
number of timestamped hyperedges: 271,233
distribution of the connected components:
Component Size, Number 

3021, 1
1, 8
Source of original data
Sources:

tags-ask-ubuntu dataset
StackExchange
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
DOI: 10.5281/zenodo.10155834
title: tags-ask-ubuntu

description: Overview
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In this dataset, nodes are tags, and hyperedges are the sets of tags applied to questions on askubuntu.com. The timestamps are in ISO8601 format and are normalized to start at 0. This dataset is derived from tags on Ask Ubuntu posts.
Statistics
Some basic statistics of this dataset are:

number of nodes: 3,029
number of timestamped hyperedges: 271,233
distribution of the connected components:
Component Size, Number 

3021, 1
1, 8
Source of original data
Sources:

tags-ask-ubuntu dataset
StackExchange
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
DOI: 10.6084/m9.figshare.24587391
title: <b>Factors controlling Sc partitioning between clinopyroxene and magma: Insights from first-principles calculations</b>

description: These materials are table 1, table 2 and supplementary file of the manuscript entitled of "Factors controlling Sc partitioning between clinopyroxene and magma: Insights from first-principles calculations".
DOI: 10.6084/m9.figshare.24587391.v1
title: <b>Factors controlling Sc partitioning between clinopyroxene and magma: Insights from first-principles calculations</b>

description: These materials are table 1, table 2 and supplementary file of the manuscript entitled of "Factors controlling Sc partitioning between clinopyroxene and magma: Insights from first-principles calculations".
DOI: 10.5281/zenodo.10155818
title: email-Enron

description: Overview
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In email communication, messages can be sent to multiple recipients. In this dataset, nodes are email addresses at Enron, and a hyperedge is comprised of the sender and all recipients of the email. Only email addresses from a core set of employees are included. Timestamps are in ISO8601 format.
This dataset was collected and prepared by the CALO Project (A Cognitive Assistant that Learns and Organizes). It contains data from about 150 users, mostly senior management of Enron, organized into folders. The corpus contains a total of about 0.5M messages. This data was originally made public and posted to the web by the Federal Energy Regulatory Commission during its investigation.
The email dataset was later purchased by Leslie Kaelbling at MIT and turned out to have a number of integrity problems. A number of folks at SRI, notably Melinda Gervasio, worked hard to correct these problems, and it is thanks to them that the dataset is available. The dataset here does not include attachments, and some messages have been deleted "as part of a redaction effort due to requests from affected employees". Invalid email addresses were converted to something of the form user@enron.com whenever possible (i.e., the recipient is specified in some parseable format like "Doe, John" or "Mary K. Smith") and to no_address@enron.com when no recipient was specified.
Statistics
Some basic statistics of this dataset are:

number of nodes: 148
number of timestamped hyperedges: 10,885
distribution of the connected components:
Component Size, Number 

143, 1
1, 5
Source of original data
Source: email-Enron dataset
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
Enron Email Dataset, William Cohen, 2015.
DOI: 10.5281/zenodo.10155819
title: email-Enron

description: Overview
This is a temporal hypergraph dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In email communication, messages can be sent to multiple recipients. In this dataset, nodes are email addresses at Enron, and a hyperedge is comprised of the sender and all recipients of the email. Only email addresses from a core set of employees are included. Timestamps are in ISO8601 format.
This dataset was collected and prepared by the CALO Project (A Cognitive Assistant that Learns and Organizes). It contains data from about 150 users, mostly senior management of Enron, organized into folders. The corpus contains a total of about 0.5M messages. This data was originally made public and posted to the web by the Federal Energy Regulatory Commission during its investigation.
The email dataset was later purchased by Leslie Kaelbling at MIT and turned out to have a number of integrity problems. A number of folks at SRI, notably Melinda Gervasio, worked hard to correct these problems, and it is thanks to them that the dataset is available. The dataset here does not include attachments, and some messages have been deleted "as part of a redaction effort due to requests from affected employees". Invalid email addresses were converted to something of the form user@enron.com whenever possible (i.e., the recipient is specified in some parseable format like "Doe, John" or "Mary K. Smith") and to no_address@enron.com when no recipient was specified.
Statistics
Some basic statistics of this dataset are:

number of nodes: 148
number of timestamped hyperedges: 10,885
distribution of the connected components:
Component Size, Number 

143, 1
1, 5
Source of original data
Source: email-Enron dataset
References
If you use this dataset, please cite these references:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
Enron Email Dataset, William Cohen, 2015.
DOI: 10.5281/zenodo.10155844
title: tags-math-sx

description: Overview
This is a temporal higher-order network dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In this dataset, nodes are tags, and hyperedges are the sets of tags applied to questions on math.stackexchange.com.
Each hyperedge corresponds to all of the tags used in a post, and each node in a hyperedge corresponds to a tag. The timestamps are normalized so that the earliest tag starts at 0 and are in millisecond resolution.
Statistics
Some basic statistics of this dataset are:

number of nodes: 1,629
number of timestamped hyperedges: 822,059
number of unique hyperedges: 174,933
Source of original data
Source: tags-math-sx dataset
References
If you use this data, please cite the following paper:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
DOI: 10.5281/zenodo.10155845
title: tags-math-sx

description: Overview
This is a temporal higher-order network dataset, which here means a sequence of timestamped hyperedges where each hyperedge is a set of nodes. In this dataset, nodes are tags, and hyperedges are the sets of tags applied to questions on math.stackexchange.com.
Each hyperedge corresponds to all of the tags used in a post, and each node in a hyperedge corresponds to a tag. The timestamps are normalized so that the earliest tag starts at 0 and are in millisecond resolution.
Statistics
Some basic statistics of this dataset are:

number of nodes: 1,629
number of timestamped hyperedges: 822,059
number of unique hyperedges: 174,933
Source of original data
Source: tags-math-sx dataset
References
If you use this data, please cite the following paper:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
DOI: 10.5281/zenodo.10155852
title: Conflict between Cultural Development and Wildlife Conservation: A Potential Threat to Reeves's Pheasant (Syrmaticus reevesii)

description: Dataset for analyses perfomed in the study accepted in Conservation Letters entitled Conflict between Cultural Development and Wildlife Conservation: A Potential Threat to Reeves's Pheasant (Syrmaticus reevesii).
DOI: 10.5281/zenodo.10155851
title: Conflict between Cultural Development and Wildlife Conservation: A Potential Threat to Reeves's Pheasant (Syrmaticus reevesii)

description: Dataset for analyses perfomed in the study accepted in Conservation Letters entitled Conflict between Cultural Development and Wildlife Conservation: A Potential Threat to Reeves's Pheasant (Syrmaticus reevesii).
DOI: 10.5519/qd.x3x23wxr
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1392471 records)
DOI: 10.5281/zenodo.10155869
title: Dataset of the Paper: Demystifying Code Snippets in Code Reviews: A Study of the OpenStack and Qt Communities and A Practitioner Survey

description: This dataset, which is composed of two parts: the code review data collected from OpenStack and Qt, and the survey data collected from industrial developers, was used to conduct an empirical study on code snippets in code reviews. A brief description of each part of the dataset is provided below:


1. Dataset (OpenStack+Qt).xlsx


contains 127,182 review comments mined from four popular projects of the OpenStack community (Nova and Neutron) and the Qt community (Qt Base and Qt Creator) from 2020 to 2021. Among the review comments, 3,197 review comments contain code snippets. In the Excel file, for the rows of review comments with code snippets, we marked the code snippets in red color as an indicator.


2. Dataset (Survey).xlsx


contains 63 valid responses to our survey questionnaire from industrial developers of OpenStack, Qt, and LinkedIn.
DOI: 10.5281/zenodo.8098561
title: Dataset of the Paper: Demystifying Code Snippets in Code Reviews: A Study of the OpenStack and Qt Communities and A Practitioner Survey

description: This dataset, which is composed of two parts: the code review data collected from OpenStack and Qt, and the survey data collected from industrial developers, was used to conduct an empirical study on code snippets in code reviews. A brief description of each part of the dataset is provided below: <strong>1. Dataset (OpenStack+Qt).xlsx</strong> contains 127,182 review comments mined from four popular projects of the OpenStack community (Nova and Neutron) and the Qt community (Qt Base and Qt Creator) from 2020 to 2021. Among the review comments, 3,197 review comments contain code snippets. In the Excel file, for the rows of review comments with code snippets, we marked the code snippets in red color as an indicator. <strong>2. Dataset (Survey).xlsx</strong> contains 63 valid responses to our survey questionnaire from industrial developers of OpenStack, Qt, and LinkedIn.
DOI: 10.25582/data.2022-02.2428217/2215068
title: Data for EMSL Project 60261 from February 2022
DOI: 10.25582/data.2022-09.2599808/2215069
title: Data for EMSL Project 60261 from September 2022
DOI: 10.25582/data.2022-09.2596153/2215070
title: Data for EMSL Project 60261 from September 2022
DOI: 10.25582/data.2022-02.2428157/2215071
title: Data for EMSL Project 60261 from February 2022
DOI: 10.25582/data.2022-05.2516260/2215072
title: Data for EMSL Project 60261 from May 2022
DOI: 10.25582/data.2022-02.2428120/2215073
title: Data for EMSL Project 60261 from February 2022
DOI: 10.25582/data.2022-02.2427441/2215074
title: Data for EMSL Project 60261 from February 2022
DOI: 10.25582/data.2022-05.2515844/2215075
title: Data for EMSL Project 60261 from May 2022
DOI: 10.25582/data.2022-08.2584172/2215076
title: Data for EMSL Project 60261 from August 2022
DOI: 10.25582/data.2022-05.2515517/2215077
title: Data for EMSL Project 60261 from May 2022
DOI: 10.6084/m9.figshare.24587406
title: (DFT )Files.zip

description: <b>DFT Summary for Hydrodehalogenation Project</b>
DOI: 10.6084/m9.figshare.24587406.v1
title: (DFT )Files.zip

description: <b>DFT Summary for Hydrodehalogenation Project</b>
DOI: 10.34740/kaggle/dsv/6157492
title: 2D-FACT - Fake Image Classification Dataset
DOI: 10.5281/zenodo.10155885
title: tags-stack-overflow

description: Overview
This dataset is derived from tags on Stack Overflow posts. Each hyperedge corresponds to all of the tags used in a post, and each node in a hyperedge corresponds to a tag. The timestamps of the posts are in millisecond resolution, are adjusted so that the time of the earliest tag starts at 0, and are in ISO8601 format.
Statistics
Some basic statistics of this dataset are:

number of nodes: 49,998
number of timestamped hyperedges: 14,458,875
number of unique hyperedges: 5,675,497
Component sizes:
Component size, number

49931, 1
2, 7
1, 53
Source of original data

tags-stack-overflow dataset
StackExchange
References
If you use this data, please cite the following paper:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.
DOI: 10.5281/zenodo.10155884
title: tags-stack-overflow

description: Overview
This dataset is derived from tags on Stack Overflow posts. Each hyperedge corresponds to all of the tags used in a post, and each node in a hyperedge corresponds to a tag. The timestamps of the posts are in millisecond resolution, are adjusted so that the time of the earliest tag starts at 0, and are in ISO8601 format.
Statistics
Some basic statistics of this dataset are:

number of nodes: 49,998
number of timestamped hyperedges: 14,458,875
number of unique hyperedges: 5,675,497
Component sizes:
Component size, number

49931, 1
2, 7
1, 53
Source of original data

tags-stack-overflow dataset
StackExchange
References
If you use this data, please cite the following paper:

Simplicial closure and higher-order link prediction. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.