The SciLake project was represented at the European Transport Conference (ETC) 2025, held from September 17-19 at the University of Antwerp. This prestigious annual conference brings together transport policy makers and researchers from across Europe and beyond to discuss the latest developments in transport policy, best practices, and research findings.

Oct 28, 2025

SciLake Contribution

Afroditi Anagnostopoulou from CERTH/HIT presented the paper titled "Transparency in maritime transportation and AIS data", co-authored with Xenophon Kitsios and Vassilis Kappatos. The presentation explored how Automatic Identification System (AIS) data can enhance transparency in maritime transportation and how it can be effectively integrated into modern solutions such as Knowledge Graphs (KGs) and AI services.

Why It Matters

Maritime transportation is essential to global trade and logistics. By using AIS data with advanced technologies like Knowledge Graphs and AI, we can enhance vessel tracking, optimize routes, improve safety, and increase transparency across the maritime sector.

This research advances SciLake's work in scientific knowledge management and data integration through our Maritime Transport pilot: https://scilake.eu/transportation-case-study-2

Conference Highlights

ETC 2025 provided excellent opportunities for networking with fellow researchers, exchanging ideas with industry practitioners, and learning about the latest innovations in European transport. The diverse program covered a broad spectrum of transport topics, from urban mobility to freight logistics and environmental sustainability.

We look forward to continuing our contributions to the transport research community and exploring new opportunities for collaboration in the future.

Daan de Graaf from Eindhoven University of Technology recently presented his doctoral research at the VLDB 2025 PhD Workshop, held as part of the 51st International Conference on Very Large Data Bases in London, United Kingdom, from September 1–5, 2025. His work, conducted within the SciLake project, addresses the challenge of integrating graph algorithms into database systems.

VLDB is one of the premier international forums for database researchers, developers, and users. Being selected to present at the PhD Workshop is a significant accomplishment that recognizes both the quality and potential impact of Daan's research. This achievement highlights the innovative work being conducted within the SciLake project and demonstrates how our research advances the state of the art in managing and analyzing large-scale scientific knowledge graphs.

Oct 28, 2025

GraphAlg: A New Language for Graph Algorithms

Daan's presentation focused on GraphAlg, a new language that makes it possible to run graph algorithms directly inside database systems. This work has important implications for the SciLake project and the broader scientific community. As graph databases become more popular for complex data analysis, current tools often lack flexibility, speed, and user-friendliness. GraphAlg solves these problems by building on well-established mathematical principles from linear algebra.

The language is designed to be easily analyzed and optimized, and it can be converted into a format that databases already understand (relational algebra). This combination makes GraphAlg both powerful and practical for real-world use.

Why This Matters for SciLake

GraphAlg is being developed specifically in the context of the SciLake project. As part of this project, the graph query engine AvantGraph will host the OpenAIRE Graph, a large scientific knowledge graph containing hundreds of millions of publications. The OpenAIRE Graph currently integrates the BIP! Ranker tool to enrich publication data with research impact indicators based on the citation graph, using algorithms typically derived from PageRank or simple citation counts.

With GraphAlg, these indicators can be computed directly within AvantGraph, replacing a complex pipeline running on a large cluster with a simpler and more efficient query with an embedded algorithm. This means:

• Significantly improved performance and reduced infrastructure requirements
• Greater flexibility for project partners to experiment with custom algorithms

This work directly supports SciLake's mission to provide advanced analytics capabilities for the scientific community.

Key Achievements and Future Directions

During his PhD research, supervised by Dr. N. Yakovets, Daan has accomplished several important milestones:

• Created the language structure and rules for GraphAlg, building on MATLANG (a mathematical framework for working with matrices)
• Built a compiler that translates GraphAlg into executable code
• Integrated GraphAlg into AvantGraph, a state-of-the-art graph query engine

In the future, Daan will work on making GraphAlg faster and more efficient, adding support for other database systems.

About the Presentation

The workshop paper, titled "Algorithm Support in a Graph Database, Done Right," was presented as part of the VLDB 2025 PhD Workshop program. The full paper is available at: https://www.vldb.org/2025/Workshops/VLDB-Workshops-2025/PhD/PhD25_5.pdf

We congratulate Daan on this achievement and look forward to following the continued development of GraphAlg as it enhances our capabilities for scientific knowledge graph analysis.

By Leily Rabbani, Richard Rosenquist, Stefania Amodeo

The International Conference on Intelligent Systems for Molecular Biology (ISMB), jointly held with the European Conference on Computational Biology (ECCB) 2025, took place in Liverpool, England from July 20-24, 2025. The event brought together approximately 2,000 participants from the global bioinformatics and computational biology community, including researchers, students, industry experts, and academics.

SciLake was proudly represented by Leily Rabbani from Karolinska Institutet, who attended on behalf of the Cancer pilot (WP5). This blog post summarizes our participation and the presentation of our SciLake’s Cancer Knowledge Graph.

Aug 18, 2025

Conference Highlights

ISMB/ECCB 2025, organized by the International Society for Computational Biology (ISCB), featured a rich program of keynote talks, specialized sessions, workshops, and poster presentations that showcased advances in computational biology.

A significant focus this year was on artificial intelligence (AI) and large language models (LLMs) in computational biology and molecular research. These themes are particularly relevant to Scilake’s interests, highlighting innovative applications of AI-driven approaches in genomics, structural biology, and data analysis.

SciLake's Cancer Knowledge Graph

Discoveries that Matter

Our pilot case explores chronic lymphocytic leukemia (CLL), the most common adult leukemia. We built our knowledge graph using data from the BloodCancerMultiOmics2017 dataset, analyzing patterns in 111 patient cases (55 aggressive and 56 indolent).

The resulting CLL knowledge graph contains over 14 million nodes and nearly 200 million relationships.

To demonstrate the practical value of our tool, we investigated TP53, a gene known to predict poor outcomes in CLL patients. Our knowledge graph revealed a previously underexplored relationship between TP53 and MAP2K4, a gene involved in cellular stress response.

This analysis identified three existing medications (mirdametinib, trametinib, and selumetinib) that target both genes, providing evidence that the MAPK/ERK pathway plays a significant role in CLL development - a finding that aligns with previous laboratory studies.

What's Next for Our Research

We are making our cancer knowledge graph even more powerful by adding:

• AvantGraph SKG-engine - to enhance how researchers can explore the data
• BIP! Spaces - to automatically extract information from scientific papers
• Gene Regulatory Networks built from different types of cancer data (including single-cell RNA sequencing and protein analysis).

Our participation at ISMB/ECCB 2025 provided valuable opportunities for networking, collaboration, and exchange of novel computational methods and biological insights, supporting both established scientists and early-career researchers. 

The SciLake project team recently presented at the OpenAIRE Connect Community Call, showcasing the Energy Pilot's work on configuring OpenAIRE gateways. This blog post summarizes key insights from Thanasis Vergoulis and Andrea Salmi's presentation on how domain experts can leverage OpenAIRE Connect to define relevant subgraphs for their research communities.

July 31, 2025  

SciLake and OpenAIRE: Building Custom Gateways for Research Communities

Thanasis Vergoulis (ARC) opened the presentation by introducing the SciLake project and explaining how OpenAIRE Connect enables domain experts to identify which parts of the OpenAIRE graph are most relevant to their specific research domains. The platform allows researchers to define and extract subgraphs that are particularly interesting or useful to their communities.

The SciLake Energy Pilot: An Iterative Configuration Approach

Andrea Salmi (HES-SO) presented the Energy Pilot's experience with configuring OpenAIRE gateways. The team adopted an iterative approach to refine their gateway configuration, testing how different criteria affected their results.

• Initial approach: Connected publications with specific projects (e.g. ENERMAPS), yielding only a few thousand results.
• Expansion phase: Added journals and selected specific journal subjects and communities, which significantly increased results to several million.
• Refinement challenge: An attempt to use advanced criteria unintentionally increased results further due to overlapping subjects.
• Successful narrowing: Removed redundant subjects and added more context in advanced criteria, helping to focus results.
• Final optimization: Implemented intensive configurations using approximately 100 carefully selected keywords for power/energy topics to achieve more precise results.

Key Findings and Recommendations

Based on their experience, the Energy Pilot team offered several valuable insights:

• Accept some noise: It's practically impossible to create a perfectly defined gateway with zero noise. The goal should be to reduce noise as much as possible while maintaining useful coverage.
• Purpose-driven configuration: Gateway configuration should align with intended use cases—whether that requires higher precision or broader coverage, particularly for transdisciplinary research.
• Technical improvements: Several suggestions were made to enhance the OpenAIRE Connect platform:
  • Streamline the process for configuring advanced criteria, possibly with table-based inputs or batch operations
  • Provide direct feedback on how different choices impact gateway results
  • Improve journal inputs, as many selected journals had minimal outputs
  • Enhance data source integration, as certain sources introduced noise while others offered minimal metadata
  • Clarify how the relevance algorithm works to help users understand result ordering
  • Implement notification systems to notify gateway managers about updates

The Energy Pilot's experience demonstrates that configuring OpenAIRE gateways is an iterative process that requires careful balancing of breadth and specificity. By sharing these insights, the SciLake team hopes to help other research communities more effectively leverage OpenAIRE Connect to create tailored research environments.