Future Library Lab

What is the Future Library Lab?

The Future Library Lab (FLL) is a team of experts with diverse but interconnected fields of expertise such as software development, artificial intelligence (AI), machine learning (ML), science information, and data science. This enables the University Library to experiment with the use of AI and ML techniques.

Who can use FLL services?

The services of the FLL are available to the following groups within Erasmus University Rotterdam (EUR):

• researchers and PhD candidates;
• research master students
• lecturers and research leaders;
• teams working with large datasets or text files.

What does this mean for your research?

The FLL can help you to:

• analyse literature faster;
• discover new research patterns;
• enrich datasets with AI;
• make complex information more accessible;
• strengthen interdisciplinary research.

Our services

AI-assisted literature review via topic identification

As a researcher, you can request assistance with literature review using machine learning (ML) and artificial intelligence (AI) tools available at the Future Library Lab. These tools make it easier and faster to identify important topics in the research, speeding up the process and allowing you to explore a wider range of studies.

AI and topic modelling can be used to quickly identify the key themes in large amounts of literature. It accelerates systematic reviews and broadens your research insight.

Patient Experience Stories

The Library hosts a large, mostly Dutch-language collection of patient experience stories on physical disabilities and diseases such as cancer, Alzheimer’s and psychosis.

This rich qualitative dataset is particularly valuable for research in health policy and citizen science.
The FLL currently collaborates with researchers from the Erasmus School of Health Policy and Management (ESHPM) to explore how this collection can be used in their projects.

Summa: data integration and enrichment

As a researcher, you can use Summa, a searchable multi-tenant platform that helps you process data from various sources. With Summa, you can ingest, transform, merge, and improve data via so-called pipelines. This platform offers you the opportunity to consult a comprehensive overview of EUR publications, enriched with an extra layer of AI-generated metadata. Additionally, Summa is designed to allow you to process other text files, such as patient experience stories, enabling you to further deepen your research.

Automatic metadata & discoverability

Future Library Lab can add AI-generated metadata to your publications to:

• improve discoverability;
• enable faster understanding of the content;
• position research more effectively.

Understandable academic texts

As a researcher, you can benefit from the application of so-called Large Language Models (LLMs), which offer simplified versions of academic publications. This technology enables you to make complex texts more accessible without losing the core or essence of the publication. This can help you especially when the original material is less accessible due to the use of jargon and complex language.

Analysis of research trends

The FLL aims to provide insight into trends within scientific research, both within and outside EUR, by merging databases such as Pure, OpenAlex, and RePEc and by using Natural Language Programming (NLP) and AI.

Research sprints & data collection

As a researcher, you can count on support with data collection via the Library's application programming interfaces (APIs) or by using web scraping. Additionally, the FLL helps you work with datasets, providing support for:

• exploratory data analysis (EDA);
• data analysis (EDA); 
• cleaning;
• analysis;
• visualization;
• text mining.

This allows you to fully focus on deepening your research.

Which workshops does the Future Library Lab offer? 

The FFL offers the following custom workshops: 

• Programming with Python (introduction).
• Programming with Python (advanced).
• Introduction to machine learning (ML). 

You can request a custom workshop by sending an email to the team.

Who does the Future Library Lab collaborate with? 

FFL supports a team of researchers at the Erasmus School of History, Culture and Communication (ESHCC) that is building a EUR large language model (LLM) in collaboration with TU Delft, as part of the Convergence project.

For staff members of Erasmus University Rotterdam

Want to know more about the Library's services on this topic? Visit the Research Support Portal for practical and detailed information. This portal is accessible to EUR staff only (via MyEUR).