Data Deposit


Data Policy

Recommended Dataset Formats

How to Deposit Data

DMP Boilerplate Language

Metadata Guidelines

README Instructions

Data Policy

The Temple University Libraries Research Data Services (RDS) team offers consultation services to help guide TUScholarShare data depositors. The team provides guidance on the format and structure of datasets to aid long-term access, discovery, and reuse. Contact RDS at

Data Definition

TUScholarShare recognizes that disciplines across the arts, humanities, social sciences, and sciences define data in markedly different ways. Accordingly, TUScholarShare understands data in broad terms across this disciplinary spectrum. TUScholarShare accepts data that were developed in support of research activities by Temple faculty, staff, and students, appropriate to each discipline. Please contact RDS ( if you have questions about whether your data is appropriate for deposit in TUScholarShare.

Need for Descriptive Data

TUScholarShare requires that depositors provide additional descriptive metadata to data deposits for the purpose of discoverability, intelligibility, reuse, and preservation. When compared to the metadata of publications such as journal articles or book chapters, data require more context-sensitive descriptions as to their origin, purpose, and use. In addition to filling out the Data Deposit Form, a README is required to accompany all data files and datasets. 

Data Privacy & Confidentiality

Depositors are required to abide by all Temple University policies relating to personal information. TUScholarShare does not accept submissions that contain any Personal Health Information (PHI), or otherwise infringe the privacy or confidentiality rights of individuals discovered inadvertently or intentionally in the data. In addition, depositors are responsible for ensuring that re-identification of any subjects from the amalgamation of the information available from all of the materials is not possible. Depositors are responsible for securing the explicit consent of human subjects described in a data deposit before the data can be shared. For additional information, please see the Withdrawal Policy.

User Norms & Code of Conduct

Depositors and researchers using TUScholarShare are expected to abide by all Temple University policies and policies governing other deposits into TUScholarShare. Users are expected to not make any attempt to re-identify any de-identified anonymized or redacted data, or otherwise violate the privacy or confidentiality rights of individuals described in the data.



Recommended Dataset Formats

Data submission in a file format listed below is strongly encouraged. The open formats are in bold.

Dataset Formats
File Extensions
  JavaScript Object Notation   .json
  Comma Separated Values   .csv
  Tab Separated Values   .tsv
  Geography Markup Language   .gml
  Keyhole Markup Language   .kml, .kmz
  GeoJSON   .geojson
  Shapefile   .shp
  WebARChive   .warc









How to Deposit Data

Depositing data presents some unique opportunities to help future researchers, and some unique challenges. See below for some guidance in depositing your data.

Deposit Checklist

  • You must be a Temple University affiliate or be sponsored by Temple to contribute work.
  • If you are new to TUScholarShare, we recommend you review our Policies.
  • Review the TUScholarShare Deposit License, and make sure your work is free from any restrictions (see our full Deposit Requirements). Consider whether you want to use the Creative Commons licensing model for your work.
  • For assistance in making a data deposit, please contact Temple University Libraries Research Data Services (RDS) team at to schedule a consultation.
  • Data Deposits will be curated by the RDS team, and delays in data curation may occur if we receive a large number of data deposits at one time, thank you for your patience.

Data Deposit Form

To deposit a single dataset, please use the Data Deposit Form

  1. Fill out your name and email address, which we will use to follow up with you. Also include your affiliation with Temple.
  2. Fill in all sections of the form that are applicable to your dataset. Good metadata will make your dataset more findable and useful. For help, see the Metadata Guidelines.
  3. The author/ copyright holder of any work deposited to TUScholarShare retains copyright to the work. To let others know how they can reuse your work, consider selecting a Creative Commons license.
  4. If the dataset being deposited has been previously published on a publisher’s website, use the SHERPA/RoMEO Database to help you determine your work’s copyright status and if there may be restrictions (e.g. an embargo period, or a publisher’s statement which must be included).
  5. Read and agree to the TUScholarShare Deposit License.
  6. Upload your file (see our Recommended Dataset Formats). Note: If the file size exceeds 12MB, submit the file as a separate attachment. To do this, ‘drop-off’ the file to via TUsafesend.
  7. Upload a README document to provide context and a guide to understanding your dataset. For help, see the README Instructions.
  8. Click ‘Submit’ to complete the deposit.
  9. You will receive an email notification from TUScholarShare staff when your work has been curated and deposited, and if any additional information is needed to complete the deposit the Research Data Services team will contact you.



DMP Boilerplate Language

If appropriate for your data, use this boilerplate language in your data management plan (DMP). It provides information about the services provided by the Temple University Libraries for continuing preservation of, and access to, research data. 


Research data generated by the project will be supported by TUScholarShare (, the institutional repository for Temple University. This is a repository service that is managed by the Temple University Libraries and uses Open Repository, an enhanced DSpace platform that is hosted by Atmire. TUScholarShare has been developed with the intent of helping researchers comply with grant-funding agency requirements. It enables dissemination and long-term preservation and curation (management, use, and re-use) of data.

Researchers will work with the University Libraries Research Data Management Services staff to facilitate the deposit of data into TUScholarShare, and to ensure appropriate metadata and complete documentation of the data to maximize the ability to understand and reuse the data. The data will be published in TUScholarShare for long-term preservation, using services such as file format migration where possible, persistent identifiers (DOIs), persistent Web addresses (handles), and checksums.

TUScholarShare data resides in two locations, a local Isilon storage system and an off-site cloud-based service, Open Repository. Open Repository’s AWS cloud storage service provides extended infrastructure, which includes a production server, test server, fallback servers, data backups, and full system backups. 



Metadata Guidelines

Depositing data to TUScholarShare requires a minimum set of depositor-supplied descriptive information (or metadata). The metadata elements below are collected in TUScholarShare to facilitate search and retrieval of your data once deposited. These guidelines are enforced in the TUScholarShare Data Deposit Form and may or may not be applicable to all submitted data.

Title of Dataset

The title of the dataset.



  • Use: Required.
  • If a formal title does not exist, create a contrived title that describes what is collected in the dataset.
  • Avoid using file names (e.g. FinalDraft_Smith.pdf) or general content descriptions (e.g. Dataset).


The name of the person(s), institution(s), group(s), or agency primarily responsible for creating this dataset.



  • Use: Required.
  • Enter author names in the order in which they should be displayed.
  • If a center, group, or organization created the dataset, enter the name in full.
  • Add one author per line, using the plus sign (+) button for entries.
  • Authors may be removed using the minus sign (-) button.

Collection Period

The time period over which the dataset was collected.



  • Use: Required.
  • Use the format YYYY or YYYY-YYYY.
  • In the case of a curated, or otherwise modified, pre-existing dataset(s), list the dates over which the author(s) compiled, curated, and modified the dataset. 
  • For example, if the author(s) worked from 2010-2012 on curating and transforming geologic mapping data from 1953-1957, the Collection Period would be 2010-2012.

Coverage Dates of Data

The time period that the data within the dataset covers.



  • Use: Required. 
  • Use the format YYYY or YYYY-YYYY.
  • For example, if the Author(s) worked from 2010-2012 on curating and transforming geologic mapping data from 1953-1957, the coverage dates would be 1953-1957.


Provide a summary or account of the content of the dataset.



  • Use: Required.
  • Summarize the dataset in one or two sentences.
  • If the dataset accompanies a journal article, enter this information here.


Provide the abstract of the published research that this dataset supports.



  • Use: Optional. 
  • Use only if the dataset being deposited to TUScholarShare is cited by or used by a published paper, including those deposited in TUScholarShare.

DOI of Paper Data Supports

Provide the Digital Object Identifier (DOI) for the published research that this dataset supports.



  • Use: Optional. 
  • Use only if the dataset being deposited to TUScholarShare is cited by or used by a published paper, including those deposited in TUScholarShare.
  • Enter the full URL (include https://).

Data Format(s)

Specify the format of your dataset. 



  • Use: Required.
  • Check all that apply.



README Instructions

In order to catalog and preserve your data for future reuse and study, we require that all data deposits include a README document. Start by downloading this template, then write your README as a plain text file and include it with your data deposit.

Please note that there is some overlap between fields in the README and fields on the Data Deposit Form, so make sure those fields are the same in both instances.

General Information

  1. Provide a title for the dataset
  2. Include all author information for contact purposes
    • For institutional authors, the Name and Institution fields may be the same or the Name field may refer to a School, Department or other organization within the institution.
    • For the Address field, use the Institution’s address, not a personal address.
    • See what an ORCID iD can do for you.
  3. Date of data collection (single date, range, approximate date)
    • This will be the same as the Collection Period field and refers to the time period over which the dataset was collected.
    • In the case of a curated, or otherwise modified, pre-existing dataset(s), list the dates over which the author(s) compiled, curated, and modified the dataset. For example, if the author(s) worked from 2010-2012 on curating and transforming geologic mapping data from 1953-1957, the Collection Period would be 2010-2012.
  4. Information about the geographic location(s) where the data was collected or generated
  5. List all funding sources and amounts that supported the data collection

Sharing/ Access Information

  1. Licenses/ restrictions placed on the data or limitations of reuse
    • This is similar to the Rights field.
    • Note the license and any restrictions on the dataset.
  2. Recommended citation for the data (see how to cite your data)
  3. Citation for and links to publications that cite or use the data
    • Provide the citation and links (DOIs if possible) for publications that cite or use this dataset.
    • If you are depositing a paper that uses the dataset in TUScholarShare, use its DOI.
  4. Links to other publicly accessible locations of the data
  5. Links/ relationships to ancillary or related datasets
    • If this dataset was derived from another dataset, based on another dataset, or other datasets were derived from it, provide links and information about the relationship to this dataset.
  6. Was data derived from another source?
    •   If yes, list source(s) - provide a lit and contextual information about the dataset(s) that this dataset was derived from.

Data & File Overview

  1. List and describe all files included in the dataset
  2. If applicable, note the relationship between files
    • For example, if a CSV was derived from a raw data file, or if a file containing code was used to transform another file.
  3. Are there multiple versions of the dataset?
    • Note any other versions of the dataset that are available in TUScholarShare, in other repositories, or if the current dataset is a newer version of an existing dataset.
    • Note what files were changed and when. 

Methodological Information

  1. Describe how the data in this dataset were collected and/ or generated
    • Include links or references to publications or other documentation containing experimental design or protocols used in data collection.
  2. Describe how the submitted data were generated from the raw or collected data
    • For example, was the data transformed or analyzed in any way?
  3. List any software- or instrument-specific information needed to interpret the data, including software and hardware version numbers
  4. If appropriate, list standards and calibration for equipment used to collect data
  5. Describe the environmental/ experimental conditions during which the data were collected
  6. Provide information about quality-assurance procedures performed on the data
  7. List the people involved in the above processes (sample collection, processing, analysis and/ or submission)

Data-Specific Information

*Repeat these sections for each applicable data file, code file, and visualization. If you have questions please contact



Last updated: Jul 9, 2020