GCM 2024

Graphs are common mathematical structures which are visual and intuitive. They constitute a natural and seamless way for system modeling in science, engineering and beyond, including computer science, life sciences, business processes, etc. Graph computation models constitute a class of very high-level models where graphs are first-class citizens. They generalize classical computation models based on strings or trees, such as Chomsky grammars or term rewrite systems. Their mathematical foundation, in addition to their visual nature, facilitates specification, validation and analysis of complex systems. A variety of computation models have been developed using graphs and rule-based graph transformation. These models include features of programming languages and systems, paradigms for software development, concurrent calculi, local computations and distributed algorithms, and biological and chemical computations. The International Workshop on Graph Computation Models aims at bringing together researchers interested in all aspects of computation models based on graphs and graph transformation. It promotes the cross-fertilizing exchange of ideas and experiences among young and senior researchers from different communities who are interested in the foundations, applications, and implementations of graph computation models and related areas.

Previous editions of the GCM series were held in Natal, Brazil (GCM 2006), in Leicester, UK (GCM 2008), in Enschede, The Netherlands (GCM 2010), in Bremen, Germany (GCM 2012), in York, UK (GCM 2014), in L’Aquila, Italy (GCM 2015), in Wien, Austria (GCM 2016), in Marburg, Germany (GCM 2017), in Toulouse, France (GCM 2018), in Eindhoven, The Netherlands (GCM 2019), online (GCM 2020 and GCM 2021), in Nantes, France (GCM 2022) and in Leicester, UK (GCM 2023).

Accepted Papers

Call for Papers

Announcement: Call for Short Papers

We are excited to announce a second round of short paper submissions. This addition is in response to some requests, and we are pleased to provide this additional opportunity to present new ideas, preliminary results, or work in progress.

Submission:

• Paper Length: Short papers should be a maximum of 4 pages, excluding the bibliography.
• Deadline: The submission deadline for short papers is May 31.
• Presentation: The presentation duration for short papers will be 10 minutes less than that allotted for regular papers (20min).

GCM 2024 solicits papers on all aspects of graph computation models. This includes but is not limited to the following topics:

Foundations

• Models of graph transformation
• Analysis and verification of graph transformation systems
• Parallel, concurrent, and distributed graph transformation
• Term graph rewriting
• Formal graph languages

Applications

• Graph-based programming models and visual programming
• Model-driven engineering
• Evolutionary computation
• Software architectures, validation and evolution
• Databases
• Graph-based security models
• Workflow and business processes
• Social network analysis
• Bioinformatics and computational chemistry
• Quantum computing
• Case-studies

Submissions and Publication

Authors are invited to submit papers in three possible categories:

1. Regular papers of at most 16 pages describing innovative contributions.
2. Short papers (work in progress, system descriptions, or position papers) of 4 pages.
3. Short announcements of 1 or 2 pages, to be presented as lightning talks of 5 minutes.

Papers in PDF format should be submitted electronically via the EasyChair system site. Submissions must use the EPTCS LaTeX style. Simultaneous submission to other conferences with proceedings, as well as submission of material that has already been published elsewhere is not allowed for regular and short papers. The page limits include references. An optional appendix may be added if this is useful for the reviewing process. If a short announcement extensively draws on already published work, a copy of that work is to be attached to the submission.

All submissions will be reviewed by the program committee; short announcements will undergo a lightweight review and mainly be assessed for their potential to stir discussion on future research of the community. Electronic proceedings will be available at the time of the workshop. The authors of selected (regular and short) papers will be invited to submit revised versions for the post-proceedings. The latter will appear in the Electronic Proceedings in Theoretical Computer Science (EPTCS).

Electronic Proceedings

Regular paper proceedings:

• Mattia De Rosa and Mark Minas:
  GrappaRE – A Tool for Efficient Graph Recognition Based on Finite Automata and Regular Expressions
• Ebtihal Althubiti and Michele Sevegnani:
  Modelling Privacy Compliance in Cross-border Data Transfers with Bigraphs
• Maram Albalwe, Blair Archibald and Michele Sevegnani:
  Modelling Real-time Systems with Bigraphs
• Nikolaus Huber and Wang Yi:
  An Encoding of Interaction Nets in OCaml
• Luca Mondada and Pablo Andres-Martinez:
  Scalable Pattern Matching in Computation Graphs
• Ziad Ismaili Alaoui and Detlef Plump:
  Linear-Time Graph Programs for Unrestricted Graphs

Lightning talk proceedings:

• Berthold Hoffmann:
  Checking Nested Graph Expressions with Alternating Finite Graph Automata
• Luca Mondada:
  A Conflict-Free Replicated Data Type for Graph Rewriting
• Adam Machowczyk and Reiko Heckel:
  Towards Graph-to-Graph Transformation Networks
• Reiko Heckel and Adam Machowczyk:
  From Message Passing to Actor Graph Neural Networks
• Francisco Martínez-Lasaca, Pablo Díez, Esther Guerra and Juan de Lara:
  Graphs in Lowcode Platforms: a Practitioner’s Approach
• Dominik Grzelak:
  Locally Explainable Rules with Bigraphs

Call for Lightning Talks

We are pleased to announce the addition of lightning talks to the GCM workshop program. Lightning Talks submissions will undergo a lightweight review and mainly be assessed for their potential to stir discussion on future research of the community. We will consider convincing lightning talks that do not recapitulate published work for invitation to submit a full paper to the post-proceedings of GCM.

Submission Guidelines

• Extended Abstract Length: Lightning talk submissions should be a maximum of 2 pages.
• Content: Contributions may be based on ideas that are of interest to GCM, regardless of whether these ideas have already been published elsewhere or are as yet unpublished.
• Presentation Slot: Accepted abstracts will be allotted a 5-minute slot for presentation during the program, followed by an open discussion.
• Submission Process: Submissions must use the EPTCS LaTeX style and be submitted electronically in PDF via the EasyChair system site.

Lightning talk submissions are invited on any topic relevant to GCM. In addition, we are planning a special session on Graph Transformation and AI with lightning talks and a panel discussion.

Graph Transformation and AI

Artificial Intelligence (AI), and Machine Learning (ML) in particular, are driving significant progress in computer applications. While ML is data-driven, AI includes rule-based symbolic approaches to modelling and automated reasoning such as in automated theorem proving, Semantic Web and Knowledge Graph technology.

Graph-like data is ubiquitous in applications, for example, in social networks, linked medical datasets, topological and geometric modelling in design, engineering and geography, software models and architectures, molecular modelling, etc.

There is significant interest in ML and AI technology utilising graph-structured data including a range of Graph Neural Network (GNN) and Graph Transformers (GT). Data in ML needs to be cleaned, integrated, mapped and translated before training and inference. This process, referred to as Data Wrangling, also applies to graph data. Hence areas where rule-based graph transformation and graph-based AI can benefit from each other include:

1. AI for Graph Transformation: Graph-based AI to address graph transformation problems, such as Inference of graphs, schemas, constraints, rules, rates and probabilities, grammars or control programs from input/output graphs, (timed) graph transition sequences, temporal graphs, or natural language requirements. Analysis, interrogation and explanation of graph transformation models, providing an alternative (e.g. NLP) interface to existing tools or interpreting models directly.
2. Graph Transformation for AI: Graph-based AI and data wrangling are graph transformations, although not usually defined in a rule-based way. GNNs operate on graphs to infer node attributes, nodes and/or edges. Rule-based graph transformations can provide a common computational model and theory. GTs are trained from examples to transform input to output graphs. A rule-based approach could raise the level of abstraction and help explainability. Graph data wrangling can benefit from concepts, theories and tools developed for model transformations, e.g. using triple graph grammars also support consistency checking, mapping, integration and translation of graph structures.

In both directions we are interested in exploring the link between Data-driven ML and symbolic AI for Graph Data where graph transformation operating on data in a rule-based way provides a link between ML and symbolic reasoning, by

• Extracting rule-based symbolic specifications from data
• Providing higher level or domain-specific input to ML in the form of rules and constraints

We invite short Lightning Talk presentations for a session on Graph Transformation and AI at GCM addressing questions such as:

• How can AI be used to address common graph transformation problems, or what are the new opportunities?
• How can rule-based graph transformation provide a platform to support, formalise, specify, analyse or implement graph-based AI?
• How can model transformation technology be adapted to graph data wrangling? What are new challenges and which solutions can be reused?
• How can rule-based graph transformation bridge the gap between symbolic AI and ML?

Contributions can discuss problems and challenges, potential application scenarios, or solution ideas.

Presentations will be followed by a panel discussion and results will be summarised in a joint paper for the post proceedings.