MQUAD Dataverse

A world of data, in a safe and secured storage space

A safe space to store survey tools, raw and processed data for future use. Dataverse provides the platform for organizing and publishing datasets, facilitating collaboration among researchers, and ensuring the long-term preservation and accessibility of research data.

It is designed for organizations to manage, share, cite, and archive their research data at a single space. Organizations can make the data available to the public or a select partners. This space also has repository of data that is publicly available which organizations can refer and engage for advancing scientific discovery across domains.

Sharing data resources can help organizations to reduce costs associated with data acquisition, storage, and analysis. Instead of each organization independently collecting and maintaining data, they can leverage shared resources, leading to cost savings.

DataWorld is a centralized and secure environment to store, manage and publish data

Data Management

Organise data with description and share datasets within a secure and user-friendly environment.

Data Versions

Store versions of datasets, track changes and document updates over time. Thereby ensuring transparency and reproducibility of research findings.

Data Access

Choose to make it public or accessible to specific collaborators for a time period.

Data Integration

Integration possible with various research tools and platforms, including statistical analysis software, data visualization tools, and academic publishing platforms. This enhances its usability and interoperability.

Data Citation

Assign identifiers to datasets which results in proper citation and credit to the owner of the work.

Data Preservation

Long term upkeep of data in a safe and reliable space, adhering to best practices for data archiving and preservation.

Data Management – organise data with description and share datasets within a secure and user-friendly environment.
Data versions – store versions of datasets, track changes and document updates over time. Thereby ensuring transparency and reproducibility of research findings.
Data Access – choose to make it public or accessible to specific collaborators for a time period.
Data Integration – integration possible with various research tools and platforms, including statistical analysis software, data visualization tools, and academic publishing platforms. This enhances its usability and interoperability.
Data Citation – assign identifiers to datasets which results in proper citation and credit to the owner of the work.
Data Preservation – long term upkeep of data in a safe and reliable space, adhering to best practices for data archiving and preservation.

Visit MQUAD Dataverse