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Data-driven analysis of research

Being a data-driven organization means using data to make fact-based and proactive decisions. KTH can gain better knowledge of how the organization is meeting its goals, and quickly identify deviations in its operations, thereby allowing it to make adjustments to work more efficiently. A strong data-driven culture promotes constant questioning and learning by using newfound insights while planning for the future.

Illustration om olika datakällor.

Research information

Research information refers to information about KTH's research and the context in which it is carried out. This can include information about researchers and their organizational affiliation, subject matter, and assignments. Additionally, it may encompass intellectual outputs, such as publications and presentations, as well as information about projects, project members, funding, and collaborative partners. At KTH, research information includes organizational structure such as department, research group, platform, and center formation. However, research data, underlying work materials and knowledge do not fall under the purview ofresearch information. You can learn more about managing research data on our research data pages .

Data analysis

Data on publication types from ABM (Annual Bibliometric Monitoring).
Data on publication types from ABM (Annual Bibliometric Monitoring).

Data analysis includes the process of collecting, analyzing, and visualizing data in order to draw conclusions. Such analyses enable decision-making, process improvement, and increased value and engagement. Data analysis ranges from basic descriptive analysis that describes what has happened to diagnostic analysis to find causes. The level of complexity and value creation increases in predictive analysis, which is used to understand what will happen, and prescriptive analysis, which describes how we should act. Data analysis provides great opportunities for new insights.

Analysis services

Data from KTH Research Information about collaborations in the world.
Data from KTH Research Information about collaborations in the world.

Learn more about analysis services  and how to use them for your specific requirements.

Many of our analyses and services are based on bibliometric data. Bibliometrics is the statistical analysis of publication data and is used as an integrated part of KTH's quality work. Bibliometric data also provides input to the various rankings performed at the international level and is therefore an important tool for establishing KTH's global relevance. Learn more about bibliometrics .

Data-driven monitoring and analysis of KTH reaserch (DAUF)

Data-driven monitoring and analysis of KTH research (DAUF) is an ongoing collaboration between the library and the IT department. The purpose of the initiative is to facilitate the monitoring and understanding of KTH's research endeavors. The services presented here are developed in dialogue with the Vice President for Research, heads of departments, and researchers at KTH. We are developing services that help school management, researchers, and support staff to better understand KTH's research.

Consultations

We offer personal consultations, participate in meetings, and conduct workshops and webinars. You can book personal consultations focused on data analysis, bibliometrics, or guidance on our services. Furthermore, we both encourage and make it our goal to answer any inquiries regarding the data sources we use and furnish access to them as necessary. Consultations can be conducted in-person, online, or via email. Kindly send an email to biblioteket@kth.se with your question and we will schedule a suitable time with you.

You are also welcome to provide feedback and suggestions for improvement to us. Two to three times a year, we hold demo meetings where you as a user can see the latest developments and provide input and feedback on our services. If you would like to receive an invitation to one of these session, please send an email to biblioteket@kth.se, and we will include you to the list.

Our team in the DAUF project