This data paper template refers to the national standards Data Paper Publishing Metadata (GB/T 42813-2023) and Academic Paper Writing Rules (GB/T 7713.2-2022), and also investigates and to some extent refers to the paper templates of domestic and foreign journals that publish data papers.

CIDU 2010 LaTeX and Microsoft Word templates.

Based on long-term research and practice, our team proposed a Journal Data Policy Template for Depositing & Sharing Paper Related Data, and it is a general data policy framework for different journals. According to the different intensities of sharing related data of papers, this policy framework divides into five levels, with the intensity decreasing from level 1 to level 5. According to the actual situation of each journal, the editorial department of the journal could select the corresponding strength level of the data policy, and then select the content of the policy text contained in this level. The V2 version of the data policy has revised the problems and optimized the first version. The V3 version has updated the data policy grading table. The V4 version has optimized the data policy grading table, partial expression and provided bilingual data policy templates in Chinese and English.

not available

This dataset is a SQLite database that accompanies methods and analysis described in the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring" (Balantic & Donovan 2019, Bioacoustics, https://www.tandfonline.com/doi/full/10.1080/09524622.2019.1605309).

A Github repository containing code for using the SQLite database also accompanies this paper at: http://github.com/cbalantic/false-positive-mitigation

GIRT-Data is the first and largest dataset of issue report templates (IRTs) in both YAML and Markdown format. This dataset and its corresponding open-source crawler tool are intended to support research in this area and to encourage more developers to use IRTs in their repositories. The stable version of the dataset contains 1_084_300 repositories, and 50_032 of them support IRTs.

This folder contains data underlying the research paper “Exploring potential contributions of open data intermediaries”. The research is about open data ecosystem and the role of open data intermediaries. The folder consists of 4 items:

1. Tentative interview questions (.pdf and .odt formats)

2. Informed consent form template (for verbal interview & written interview) (.pdf and .odt formats)

3. De-identified interview transcripts (.pdf and .odt formats)

4. Coding results (.pdf and .ods formats)

Note about the tentative interview questions:

The interviews were conducted between May and July 2023 based on the semi-structured approach. We customise the tentative interview questions accordingly for each interview and share them with the interviewees in advance (for the majority, at least three working days in advance). As semi-structured interviews, the ultimate interview questions may differ from the tentative questions based on the information provided by the interviewees and time constraints (refer to item #3).

Note about the informed consent form:

We sent the informed consent form to every interviewee in advance and requested them to return it to us before the interview. The consent form has been reviewed by TU Delft's Human Research Ethics Committee (HREC).

Note about the de-identified interview transcripts (and coding results):

The de-identified interview transcripts should be read in the context of the research on open data ecosystem and the role of open data intermediaries. We removed personally identifiable information from the transcripts. A few interviewees may risk being identifiable if their organisation is known. Hence, we removed the identification of the organisation and country in all transcripts. Partially disclosing the organisation or country for some transcripts increases the risks of identifying the non-disclosed transcripts. With verbal communication, some sentences may be less incomprehensible in writing. Thus, we did minimal edits when transcribing to improve the comprehensibility where necessary, but the main objective was to keep the transcript as close to verbatim as possible. All interviewees whose interview transcripts are recorded in this document give permission for the anonymised transcript of their interview, with personally identifiable information redacted, to be shared in 4TU.ResearchData repository so it can be used for future research and learning.

Acknowledgement:

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.

Data underlying research paper “Developing an open data intermediation business model: insights from the case of Esri”

by Ashraf Shaharudin, Bastiaan van Loenen, and Marijn Janssen from Delft University of Technology (TU Delft), the Netherlands.

This folder contains data underlying the research paper “Developing an open data intermediation business model: insights from the case of Esri”. It consists of:

1. De-identified interview transcripts

2. Informed consent form template

Note about the de-identified interview transcripts:

The de-identified interview transcripts should be read in the context of the research on open data ecosystem and the role of Esri as open data intermediaries.

The 27 interviews, involving 29 interviewees, were conducted between April 2023 and April 2024 based on the semi-structured approach. We shared the tentative interview questions with the interviewees in advance (for the majority, at least three working days prior). Since they are semi-structured interviews, the ultimate interview questions may differ from the tentative questions.

We removed personally identifiable information from the transcripts. Some interviewees may risk being identifiable if their organization is known. Hence, we removed the organization and country information from all transcripts.

With verbal communication, some sentences may be less incomprehensible in writing. Thus, we did minimal edits when transcribing to improve the comprehensibility where necessary, but the main objective was to keep the transcripts as close to verbatim as possible.

Note about the informed consent form template:

We sent the informed consent form to every interviewee in advance and requested that they return it to us before or during the interview.

All interviewees whose interview transcripts are recorded in this document give permission for the anonymized transcript of their interview, with personally identifiable information redacted, to be shared in 4TU.ResearchData repository so it can be used for future research and learning.

Acknowledgement:

This research is part of the 'Towards a Sustainable Open Data ECOsystem' (ODECO) project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.

This dataset contains the raw data used for the paper: 'Optimal spectral templates for triggered feedback experiments' submitted to PLoS One.

Template for a Hypothesis Description paper

Crello dataset consists of design templates obtained from online design service, crello.com. The dataset contains designs for various display formats, such as social media posts, banner ads, blog headers, or printed posters, all in a vector format. In dataset construction, design templates and associated resources (e.g., linked images) from crello.com were first downloaded. After the initial data acquisition, the data structure was inspected and identified useful vector graphic information in each template. Next, mal-formed templates or those having more than 50 elements were eliminated, resulting in 23,182 templates. The data was paritioned to 18,768 / 2,315 / 2,278 examples for train, validation, and test splits.

The data set includes source code that implements a PBPK template model applicable to PFAS. It includes data digitized from Kim et al. (2018), Kim et al. (2019), and Loccisano et al. (2012) used to show the capability of the template to replicate published PFAS PBPK models. The template model is described in a paper that is in review at the journal Toxicological Sciences.

Data that was used for prediction of groundwater levels in the paper: https://doi.org/10.1016/j.spasta.2023.100740 Lineage: This data was assembled from data collected for the following research: https://doi.org/10.1016/j.gsd.2023.100964 https://doi.org/10.1016/j.ejrh.2023.101500

This resource is a metadata compilation for technical reports and papers used to interpret data collected during the DOE AASG National Geothermal Data System Supplemental Data project by the Utah Geological Survey. The compilation is published as an Excel workbook containing header features including title, description, author, citation, originator, distributor, and resource URL links to documents for download. The Excel workbook contains 6 worksheets, including information about the template, notes related to revisions of the template, resource provider information, the data, a field list, and vocabularies (data valid terms) used to populate the data worksheet. This resource was provided by the Utah Geological Survey and made available for distribution through the National Geothermal Data System.

Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.

This dataset was used in the paper 'Template-based Abstractive Microblog Opinion Summarisation' (to be published at TACL, 2022). The data is structured as follows: each file represents a cluster of tweets which contains the tweet IDs and a summary of the tweets written by journalists. The gold standard summary follows a template structure and depending on its opinion content, it contains a main story, majority opinion (if any) and/or minority opinions (if any). Additionally, we will include the abstractive model baselines we have used in the paper.For ease of use, we distinguish between opinionated/non-opinionated and training/testing/agreement sets.Due to the recent changes in the availability of the Twitter / X academic API, please reach out to iman.bilal@warwick.ac.uk if you consider using the dataset.License: The annotations are provided under a CC-BY license, while Twitter retains the ownership and rights of the content of the tweets.

This is the data set for a series of interviews in chemistry on data management (plans) and presents interim results. A more detailed analysis and description can be found in the paper "Road to a Chemistry-specific Data Management Plan" submitted to Data Science Journal (2022-12-15). The interview series will continue in 2023 and final results will be published later in 2023. The aim of the conducted interview series is the enrichment of the online survey data from the RDA WG Discipline-specific Guidance for DMP and in a second step the development of a chemistry-specific data management plan template. For this purpose, the current status of data management as well as information about the workflows in the various chemical disciplines were requested in a personal interview with 22 participants so far. All the gathered information and examples will be used to develop a DMP template or guide in line with chemistry-specific requirements. The results provide a comprehensive outlook on the future developments of RDM in chemistry. Possible strategies for implementation are also discussed.

Koncile reads your powers of attorney (paper or scanned) and extracts key data from them: principal, mandatary, object, duration, date, signatures. Structured export via Excel, JSON or API.

A snowpit analysis template developed during Hansbreen Snowpit Database preparation.

Relying on the enclosed files will enable the efficient use of the Interactive Snow Profile Visualizer niViz software (https://niviz.org) and achieve interoperable final products. ZIP catalogue contains the following filenames extensions: A) PDF – used to print table template on a waterproof paper (A4 or A5 format) and provide collecting the complete range of data during fieldwork; B) XLS – used for data archiving. Contained formulas automatically calculate the thickness and snow water equivalent of subsequent layers.

All information regarding the snow data harmonization on Hansbreen will be available in the journal article: Laska M., Luks B., Kępski D., Gądek B., Głowacki P., Puczko D., Migała K., Nawrot A., Pętlicki M. Hansbreen Snowpit Dataset – over 30-year of detailed snow research on the Arctic glacier. Scientific Data [submitted]

All collected data will be available via the PANGAEA Data Publisher: Laska M., Luks B., Kępski D., Gądek B., Głowacki P., Puczko D., Migała K., Nawrot A., Pętlicki M. Hansbreen Snowpit Dataset: a long-term snow monitoring (1989–2021) in the unique field laboratory (SW Spitsbergen, Svalbard). PANGAEA Data Publisher [in review]

The content of the replication package is the following:Issue History of 100 Projects.zip:For each project, there is a JSON file that contains information about the history of each issue.repos.zip:For each project, there is a .git folder that contains the repository content.code.zip:Code for mining, analyzing, and reporting for our research can be found in this zipped folder.Reports.zip:Contains the figures that are generated by our code and used in the paper.Research Survey - Issue Templates on GitHub (Responses) - Shared.pdfContains the questions and answers to our research survey.