AI-based tools to support research data management

As datasets grow in size and complexity, traditional methods of data management may be insufficient to meet the demands of modern research. This is where AI-based tools can come into play, offering a suite of powerful capabilities to streamline and enhance data management processes. These tools are designed to address a variety of challenges that researchers face, from data collection and cleaning to storage, analysis, and security. The integration of AI in research data management can enable researchers to focus on higher-level like tasks such as hypothesis generation and theory building, whilst helping maintain scientific reproducibility. But despite these advantages, it is important to recognise that AI tools are not a panacea, and present both opportunities and threats to open research. For example, they require careful selection and implementation to address specific research needs, and the reliance on AI necessitates a degree of proficiency in data science, which might be a barrier for some researchers. There can also be concerns over data reuse, and questions about the motivations of major-league software developers. Nonetheless, we’ve noticed some AI-based software tools that seem to be achieving prominence. Below is a list of these. They are not intended as recommendations, but may provide a starting point for critical evaluation.

Finally, an interesting perspective on the use of AI in science was provided by UoB’s Pen-Yuan Hsing in his recent talk at the Reproducibility by Design symposium in Bristol on 26th June: “AI is not the problem – thinking about outcomes”.

Data Collection and Integration

Google Data Studio

Google Data Studio allows researchers to turn data into informative, easy-to-read, shareable, and customisable dashboards and reports. Its AI capabilities help integrate and visualize data from multiple sources.


Keboola leverages AI to integrate various data sources, automate workflows, and ensure data consistency, aiding researchers in managing complex datasets.

Data Cleaning and Preparation


Trifacta uses AI to simplify data wrangling, helping researchers clean and prepare their data for analysis. It identifies patterns and anomalies.


Talend provides AI-powered data integration and data integrity solutions, allowing researchers to clean, transform, and govern data efficiently.

Data Storage and Management

Datalore by JetBrains

Datalore is an AI-driven collaborative data science platform that allows researchers to create, run, and share Jupyter notebooks in the cloud.

Azure Data Lake

Azure Data Lake provides a scalable and secure data storage solution, with AI capabilities to manage large datasets and perform big data analytics.


RapidMiner uses AI to facilitate data mining, machine learning, and predictive analytics. It offers a visual workflow designer for data preparation, model building, and evaluation.


KNIME Analytics Platform is an open-source software that integrates various components for machine learning and data mining through a modular data pipelining.

Leave a Reply

Your email address will not be published. Required fields are marked *