A Study on interoperable bidirectional graph transformations

研究成果の概要 (和文) : データの相互変換は情報システムにおける重要な操作であるが、双方向変換は、その変換をこえて双方向に更新を伝播させることができる。本研究は、双方向変換の(1)他の枠組への組み込み、(2)他のシステムと対等で相補的な統合、(3)双方向変換システム自身への他のシステムの組み込みに必要な相互運用性という三つの相互運用性を通して、扱うグラフの表現力の向上、変換の性能や能力の向上等を目指し、単方向変換の部分翻訳に基づく部分双方向化の枠組、枝間の順序の導入による記述能力の向上、双方向変換のモジュール性につながる変換の加法性の提案などの成果が得られた。研究成果の概要 (英文) : Data transformation plays an important role in various information systems. Bidirectional transformations are a mechanism to propagate updates bidirectionally over such transformation. This project aims at enhancing interoperability of bidirectional transformations by (1) embedding in other systems, (2) complementary integration with other systems and (3) embedding other systems into bidirectional transformation systems themselves, to achieve expressive power of graph data model, performance and expressive power of transformations. We have proposed partial bidirectionalization framework through partial translation, bidirectionalization of ordered graphs, additivity of transformation for modularity of transformations, among other things

The Lannion report on Big Data and Security Monitoring Research

International audienceDuring the last decade, big data management has attracted increasing interest from both the industrial and academic communities. In parallel, Cyber Security has become mandatory due to various and more intensive threats. In June 2022, a group of researchers has met to reflect on their community's impacts on current research challenges. In particular, they have considered four dimensions: (1) dedicated systems being data processing and analytic platforms or time series management systems; (2) graphs analytics and distributed computation; (3) privacy; and (4) new hardware