The PolyU Research Data Repository (Beta)

Research Data Deposits for Various Scenarios

The PolyU Research Data Repository allows researchers to deposit and share data for diverse scenarios. Here are the types of research data that can be deposited based on different contexts:

Journal Publications:

• Raw data and processed data relevant to the publication
• Supplementary materials, such as figures, tables, and charts
• Methodology and experimental protocols
• Code or scripts used for analysis or simulations
• Supporting documentation and metadata

Pre-Publication Reviews:

• Preprints or draft versions of the research manuscript
• Associated datasets and results
• Supporting materials, including figures, tables, and additional analyses
• Methodological details and protocols
• Relevant metadata and documentation

Patent Applications:

• Experimental data and results supporting the patent claims
• Prototypes, designs, or schematics
• Methodology and detailed experimental procedures
• Supporting documentation, including patent application drafts and related materials
• Metadata and documentation describing the data and its relationship to the patent application

Collaborative Research Projects:

• Data generated by multiple research teams or institutions
• Interdisciplinary datasets and findings
• Project reports, meeting minutes, and progress updates
• Research instruments, surveys, or questionnaires
• Documentation describing the collaboration and data sharing agreements

Theses and Dissertations:

• Data collected during the research process
• Analysis results and findings
• Supporting materials, such as survey instruments or interview transcripts
• Methodological details and protocols
• Relevant metadata and documentation

What can I deposit?

The PolyU Research Data Repository welcomes a wide range of research data, including:

• Quantitative, qualitative, geospatial, multimedia, simulation and modeling data etc.
• Comprehensive metadata and documentation alongside the datasets for better readability and potential reuse

Be aware of a few precautions and limitations when uploading your data:

• Max. file number per dataset: 100
• Max. individual file size: 1GB
• File format
  • See below for the recommended formats
  • Executable programs or scripts (e.g., exe, bat, vbs) are NOT allowed
• Any sensitive or confidential data must be appropriately anonymized or de-identified before deposition to ensure compliance with ethical and legal requirements
• For full-text of your research outputs, please submit to The PolyU Institutional Research Archive (PIRA) instead

If you have special file number, size and format needs, please contact us.

Recommended File Format

File format selection is a crucial consideration when aiming for long-term accessibility of your research data. Ideally, the chosen file format should possess the following characteristics:

• Non-proprietary: Opt for file formats that are open source and not subject to proprietary restrictions.
• Open documentation: Ensure that the file format has well-documented specifications, promoting transparency and ease of understanding.
• Wide adoption: Select a file format that is widely adopted and recognized within the research community, enhancing interoperability and future accessibility.
• Software compatibility: Choose a file format that can be opened and utilized by multiple software applications, minimizing dependencies on specific software tools.
• Compression considerations: Prefer file formats that employ either no compression or lossless compression techniques, allowing for reduced file sizes without compromising data quality.
• Avoid embedded scripts or files: To ensure stability and compatibility, refrain from using file formats that incorporate embedded scripts or files.

While it may not always be possible to find a file format that meets all the criteria mentioned above, it is advisable to safeguard your data by saving it in multiple formats whenever feasible. This approach ensures redundancy and adaptability, mitigating risks associated with format obsolescence over time.

The table below provides guidance on the recommended and accepted file formats for data sharing, reuse, and preservation within the PolyU Research Data Repository:

Data Type	Recommended formats	Acceptable formats
Spreadsheets	CSV (.csv) Tab-delimited File(.tab)	Microsoft Excel (.xls, .xlsx) Open Document Spreadsheet (.ods)
Statistical Data	SPSS (.sav) STATA (.dta) SAS (.sas7dat) DDI (.xml)	SPSS Portable (.por)
Databases	SQL (.sql) SIARD (.siard) CSV (.csv) XML (.xml)	Microsoft Access (.mdb, .accdb) dBase (.dbf) HDF5 (.hdf5, .he5, .h5)
Text	PDF/A (.pdf) ODT (.odt) Unicode text (.txt) Rich Text File (.rtf)	Microsoft Word (.doc, .docx) PDF other than PDF/A (.pdf) Non-Unicode text (.txt)
Images	TIFF (.tif, .tiff)	Photoshop files (.psd) PDF (.pdf) JPEG (.jpg, .jpeg, .jp2) PNG (.png)
Audio	FLAC (.flac)	WAVE (.wav) MP3 (.mp3) AAC (.aac, .m4a) AIFF (.aif, .aiff) OGG (.ogg)
Video	MPEG-4 (.mp4) Matroska (.mkv)	Window Media Video (.wmv) QuickTime (.mov, .qt)

You may also find more recommended and acceptable file formats for other types of data from UK Data Service.

     
   Image CC-BY-SA by SangyaPundir         

Ensure your Data as FAIR as possible!

To make your shared data useful, your data should be as FAIR as possible. FAIR stands for Findable, Accessible, Interoperable, and Reusable. It is a set of guiding principles formulated by Force11, aiming at optimizing discovery and reuse of research data.

FAIR data is a framework for you to manage your research data to be shared so that other researchers will be able to find it, understand it, and reuse it effectively. Below is a simplified description of what is FAIR. We encourage you to read the original document for details. 

►  Findable

►  Accessible

►  Interoperable

►  Reusable

Depositing your research data in a data repository is a good way to help your data to be FAIR, as these data repositories usually will assign DOI to your data, populate the metadata and assist you to specify the reuse license of your data.