#Password repository cloud solution software#
The Dataverse software has been developed since 2006 at the Institute for Quantitative Social Science at Harvard University.
Dataverse provides additional features such as versioning of datasets, customized virtual repositories within the same hosting infrastructure, multiples roles and permissions to support data management and curation, tiered access based on granted permissions, and APIs to deposit, explore, or visualize the data. The Dataverse repository platform enables the building of repositories without having to implement from scratch all the standards and best practices needed to fully support data sharing and archiving.
#Password repository cloud solution how to#
a Digital Object Identifier or DOI)ģ) Well-defined restrictions, licenses and terms of use to know how to access the dataĤ) Rich metadata describing the dataset to help find it and reu se it (see Joint Declaration of Data Citation Principles and FAIR principles). Each dataset must have:ġ) A data citation to credit data authorsĢ) A registered global persistent identifier to locate and reference the dataset indefinitely (e.g. The research community has developed standards and best practices to incentivize and improve the quality of data sharing. This is driven by a number of factors, including recent open data policies, funder and journal requirements, and community awareness for the need of reproducibility of a scientific claim, which require access to the data. Finally, access to metadata associated with the dataset is key to find and reuse the data.ĭata sharing is being adopted in many scientific communities as the way to make data accessible to others. Also, the effort to curate and make a dataset available can be enormous, and it is becoming critical to provide a mechanism to give dataset authors credit for this work.
Having a mechanism where users can locate datasets and apply for access is critical to making these datasets available. For example, some agencies require dataset users to sign a term of use so that the agency is not liable for fully anonymizing the dataset. In our experience, many data owners, while willing to widely share datasets, are uncomfortable with a-priori making them fully public. While AWS's public datasets service demonstrates the value of integrating access to datasets with cloud computing, it lacks the power of today's fully functional research data repositories, which follow best practices on data sharing.
However, this is not a satisfying solution for data repositories stakeholders. Rather than having to spend hours downloading these datasets, AWS users can browse the AWS repository, locate a dataset, and then analyze it in-situ using Amazon Elastic Map Reduce. Amazon hosts a variety of public datasets that range from census data, to an inventory of Google Books, to Human Genome information. To understand the value of converging data repositories and cloud computing, consider the popular AWS public dataset service. Equally, there has been an increase in the use of open source software for creating private and open clouds (e.g., OpenStack and OpenNebula), as well as in the use of commercial public clouds (e.g., Amazon Web Services, Microsoft Azure, Google Cloud), by academia, government, and businesses alike. According to the re3data website, there are now more than 1,800 public research data repositories used in academia, government, and business, supported by either open-source repository platforms (e.g., Dataverse, DSpace, CKAN, and Fedora), proprietary software (e.g., Figshare), or one-off databases (e.g., Protein Data Bank). In the last decade, the use of data repository and cloud platforms have grown significantly but mostly separately, not taking advantage of one another. At the time of Big Data, when large and streaming datasets are becoming more common, it is necessary for repository and cloud platforms to converge so that data do not need to be moved constantly when they are processed, shared, and archived. The Harvard Dataverse repository alone hosts more than 70,000 datasets with contributions from 500 research and academic institutions worldwide Imagine combining the power and scalability of cloud computing and storage with access to thousands of datasets hosted in a reliable and feature-rich data repository platform? Cloud Dataverse does exactly that-brings a mature and widely used data repository platform, Dataverse, together with the OpenStack cloud platform. Mercè Crosas, Ph.D., Chief Data Science & Technology Officer, Harvard University
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