Natallia Kokash

Natallia Kokash, Leonid Makhnist

In this paper, we address an issue of finding explainable clusters of class-uniform data in labelled datasets. The issue falls into the domain of interpretable supervised clustering. Unlike traditional clustering, supervised clustering aims at forming clusters of labelled data with high probability densities. We are particularly interested in finding clusters of data of a given class and describing the clusters with the set of comprehensive rules. We propose an iterative method to extract high-density clusters with the help of decisiontree-based classifiers as the most intuitive learning method, and discuss the method of node selection to maximize quality of identified groups.

Natallia Kokash, Adam Belloum, Paola Grosso

Federated data processing (FDP) offers a promising approach for enabling collaborative analysis of sensitive data without centralizing raw datasets. However, real-world adoption remains limited due to the complexity of managing heterogeneous access policies, regulatory requirements, and long-running workflows across organizational boundaries. In this paper, we present a framework for compliance-aware FDP that integrates policy-as-code, workflow orchestration, and large language model (LLM)-assisted compliance management. Through the implemented prototype, we show how legal and organizational requirements can be collected and translated into machine-actionable policies in FDP networks.

Natallia Kokash, Bernard de Bono, Tom Gillespie

We are developing infrastructure to support researchers in mapping data related to the peripheral nervous system and other physiological systems, with an emphasis on their relevance to the organs under investigation. The nervous system, a complex network of nerves and ganglia, plays a critical role in coordinating and transmitting signals throughout the body. To aid in this, we have created ApiNATOMY, a framework for the topological and semantic representation of multiscale physiological circuit maps. ApiNATOMY integrates a Knowledge Representation (KR) model and a suite of Knowledge Management (KM) tools. The KR model enables physiology experts to easily capture interactions between anatomical entities, while the KM tools help modelers convert high-level abstractions into detailed models of physiological processes, which can be integrated with external ontologies and knowledge graphs.

Natallia Kokash

Reo, an exogenous channel-based coordination language, is a model for service coordination wherein services communicate through connectors formed by joining binary communication channels. In order to establish transactional communication among services as prescribed by connector semantics, distributed ports exchange handshaking messages signalling which parties are ready to provide or consume data. In this paper, we present a formal implementation model for distributed Reo with communication delays and outline ideas for its proof of correctness. To reason about Reo implementation formally, we introduce Timed Action Constraint Automata (TACA) and explain how to compare TACA with existing automata-based semantics for Reo. We use TACA to describe handshaking behavior of Reo modeling primitives and argue that in any distributed circuit remote Reo nodes and channels exposing such behavior commit to perform transitions envisaged by the network semantics.

Natallia Kokash, António Ravara

Welcome to the proceedings of FOCLASA 2012, the 11th International Workshop on the Foundations of Coordination Languages and Self-Adaptation. FOCLASA 2012 was held in Newcastle upon Tyne, UK, on September 8, 2012 as a satellite event of CONCUR 2012, the 23rd International Conference on Concurrency Theory. The workshop provides a venue where researchers and practitioners could meet, exchange ideas, identify common problems, determine some of the key and fundamental issues related to coordination languages and self adaptation, and explore together and disseminate solutions. Indeed, a number of hot research topics are currently sharing the common problem of combining concurrent, distributed, mobile and heterogeneous components, trying to harness the intrinsic complexity of the resulting systems. Computation nowadays is becoming inherently concurrent, either because of characteristics of the hardware (with multicore processors becoming omnipresent) or due to the ubiquitous presence of distributed systems (incarnated in the Internet). Computational systems are therefore typically distributed, concurrent, mobile, and often involve composition of heterogeneous components. To specify and reason about such systems and go beyond the functional correctness proofs, e.g., by supporting reusability and improving maintainability, approaches such as coordination languages and self adaptation are recognised as fundamental. This year, we received 13 submissions involving 35 authors from 10 different countries. Papers underwent a rigorous review process, and all accepted papers received 3 review reports. After the review process, the international Program Committee of FOCLASA 2012 decided to select 8 papers for presentation during the workshop and inclusion in these proceedings. These papers tackle different issues that are currently central to our community, self-adaptation and coordination, processes and coordination, and type systems. The workshop features an invited talk by Sebastian Uchitel from Imperial College London (UK).