What are the latest data management trends and tools for research management?

2 Data integration

Data integration is the process of combining and harmonizing data from different sources and formats, such as surveys, experiments, observations, simulations, and sensors. Data integration can help you enrich, validate, and analyze your data, as well as discover new insights and patterns. Data integration can also enable cross-disciplinary and cross-institutional research, as well as foster open science and data sharing. Data integration can be facilitated by various tools and techniques, such as data pipelines, data lakes, data warehouses, and data virtualization.

3 Data visualization

Data visualization is the practice of presenting and communicating data in graphical or interactive forms, such as charts, maps, dashboards, and stories. Data visualization can help you explore, understand, and interpret your data, as well as convey your findings and recommendations to your audience. Data visualization can also enhance the engagement, impact, and dissemination of your research, as well as stimulate feedback and discussion. Data visualization can be achieved by various tools and platforms, such as Tableau, Power BI, R Shiny, and Flourish.

4 Data analytics

Data analytics is the application of statistical, computational, and machine learning methods to extract and generate value from data, such as descriptive, predictive, and prescriptive analytics. Data analytics can help you test hypotheses, identify trends and correlations, evaluate outcomes and impacts, and optimize decisions and actions. Data analytics can also support innovation, creativity, and problem-solving in your research, as well as reveal new opportunities and challenges. Data analytics can be performed by various tools and languages, such as Python, R, SAS, and SPSS.

5 Data literacy

Data literacy is the ability to access, understand, evaluate, and use data effectively and responsibly in research and beyond. Data literacy can help you enhance your data management skills and competencies, as well as your critical thinking and reasoning abilities. Data literacy can also empower you to participate in and contribute to the data-driven society and economy, as well as the data culture and community. Data literacy can be developed and improved by various resources and initiatives, such as online courses, workshops, webinars, and peer networks.

6 Data sustainability

Data sustainability is the aspiration and action to ensure the long-term preservation, accessibility, and reuse of data, as well as the recognition and reward of data producers and users. Data sustainability can help you increase the impact and visibility of your research, as well as the return on investment of your data. Data sustainability can also benefit the scientific and social progress and development, as well as the ethical and responsible use of data. Data sustainability can be supported and promoted by various mechanisms and incentives, such as data repositories, data citations, data badges, and data policies.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?