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Text-attributed graphs (TAGs) have become a key form of graph-structured data in modern data management and analytics, combining structural relationships with rich textual semantics for diverse applications. However, the effectiveness of analytical models, particularly graph neural networks (GNNs), is highly sensitive to data quality. Our empirical analysis shows that both conventional and LLM-enhanced GNNs degrade notably under textual, structural, and label imperfections, underscoring TAG quality as a key bottleneck for reliable analytics. Existing studies have explored data-level optimization for TAGs, but most focus on specific degradation types and target a single aspect like structure or label, lacking a systematic and comprehensive perspective on data quality improvement. To address this gap, we propose LAGA (Large Language and Graph Agent), a unified multi-agent framework for comprehensive TAG quality optimization. LAGA formulates graph quality control as a data-centric process, integrating detection, planning, action, and evaluation agents into an automated loop. It holistically enhances textual, structural, and label aspects through coordinated multi-modal optimization. Extensive experiments on 5 datasets and 16 baselines across 9 scenarios demonstrate the effectiveness, robustness and scalability of LAGA, confirming the importance of data-centric quality optimization for reliable TAG analytics.

Crime is one of the greatest threats to urban security. Around 80 percent of the world's population lives in countries with high levels of criminality. Most of the crimes committed in the cities take place in their urban environments. This paper presents the development and validation of a digital shadow platform for modeling and simulating urban crime. This digital shadow has been constructed using data-driven agent-based modeling and simulation techniques, which are suitable for capturing dynamic interactions among individuals and with their environment. Our approach transforms and integrates well-known criminological theories and the expert knowledge of law enforcement agencies (LEA), policy makers, and other stakeholders under a theoretical model, which is in turn combined with real crime, spatial (cartographic) and socio-economic data into an urban model characterizing the daily behavior of citizens. The digital shadow has also been instantiated for the city of Malaga, for which we had over 300,000 complaints available. This instance has been calibrated with those complaints and other geographic and socio-economic information of the city. To the best of our knowledge, our digital shadow is the first for large urban areas that has been calibrated with a large dataset of real crime reports and with an accurate representation of the urban environment. The performance indicators of the model after being calibrated, in terms of the metrics widely used in predictive policing, suggest that our simulated crime generation matches the general pattern of crime in the city according to historical data. Our digital shadow platform could be an interesting tool for modeling and predicting criminal behavior in an urban environment on a daily basis and, thus, a useful tool for policy makers, criminologists, sociologists, LEAs, etc. to study and prevent urban crime.

Passionate about digital, data, IoT or AI and willing to help a dynamic and ambitious team on a human scale? For more than 15 years, we have been advising companies and administrations and supporting them in the implementation of their transformation projects in France and abroad. To do so, we rely both on technological leverage and on the strength of our DNA based on collective intelligence, agility and entrepreneurial spirit. With a presence on five continents and more than 3,500 employees, our goal is to reach more than a €1 billion revenue by 2024. Innovation is at the heart of our development and we are involved in areas linked to the technological changes of major groups, such as Big Data, IoT, Blockchain and Artificial Intelligence.

Version 1 is celebrating 25 years in the IT industry this year and we continue to be trusted by global brands to deliver IT solutions that drive customer success. Version 1 is not just a Microsoft Gold Partner, an AWS Premier Consulting Partner and an Oracle Platform Partner; we are also an award-winning employer and our employees are at the heart of Version 1. We invest in a strong culture of wellness through programs that help our employees create their journey toward optimal wellbeing. This framework is based on the'Strength in Balance' theme and this is seen again in our Diversity, Inclusion and Belonging Team motto "Bring Your Difference". As the volume of data managed by Version 1 customers continues to grow, many organisations struggle with defining their strategy, and shaping the technology solutions that will enable them to fully realise the value of the data they hold.