Konferenzen  >  Informatik  >  Informations & Wissensmanagement, Big Data Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In today’s digital landscape, complexity grows with increasing data volume and degree of interconnection. A suitable data abstraction is crucial for comprehending and navigating this dense network of connections. Starting from Euler’s pioneering work on The Bridges of Konigsberg in 1735, graphs have steadily evolved as a robust and adaptable conceptual framework. Graphs are universal representations of concepts, where nodes are markers for distinct entities and edges delineate their interrelations, further enriched with detailed annotations when necessary. Graphs are successful in various domains, like bioinformatics, e-commerce, logistics and transportation networks, urban planning, and even pandemic analysis or vaccine development (e.g., during COVID-19).

ETPUB

2025 the 3rd International Conference on Intelligent Control and Computing (IC&C 2025) will take place in Changchun, China, from April 25 to 27, 2025. The goal of this conference is to foster pure and applied researches in recognition of academic and industry, and to encourage interdisciplinary and international collaboration for the participants.The conference would be an ideal platform for keeping up with advances and changes to a consistently morphing field, we sincerely look forward to some exemplary and inspirational project experiences and innovations.

Email: helen@academic.net

Autonomous Systems; Decision Support Systems; Learning and Adaptive Control Systems; Intelligent Fault Detection and Identification; Intelligent Control Theory and Applications; Network Intelligence and Network Control; Hybrid Intelligent Systems; Neural Networks Based Control Systems; Fuzzy Control;

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

The increasing amount of data being collected, stored, and analyzed induces a need for efficient, scalable, and robust methods to handle this data. Representation learning, i.e. the practice of leveraging neural networks to obtain generic representations of data objects, has been shown effective for various applications over data modalities such as images and text. More recently, representation learning has shown initial impressive capabilities on structured data (e.g. relational tables in databases), for a limited set of tasks in data management and analysis, such as data cleaning, insight retrieval, and data analytics. Most applications traditionally relied on heuristics and statistics, which are limited in robustness, scale, and accuracy. The ability to learn abstract representations across tables unlocked new opportunities, such as pretrained models for data augmentation and machine learning, that address these limitations. This emerging research area, which we refer to as Table Representation Learning (TRL), receives increasing interest from industry as well as academia , in particular in the communities of data management, machine learning, and natural language processing. This growing interest is a result of the high potential impact of TRL in industry given the abundance of tables in the organizational data landscape, the large range of high-value applications relying on tables, and the early state of TRL research so far.

ICBDC2025 is technically sponsored by Sensors and System Society of Singapore, Newcastle Australia Institute of Higher Education Pte Ltd, Singapore, supported by Harbin Engineering University, China.

2025 10th International Conference on Big Data and Computing (ICBDC 2025) will be held during May 16-18, 2025 in Singapore. The aim of ICBDC 2025 is to present the latest research and results of scientists related to Big Data and Computing topics.

Email: Dunn@iact.net

Algorithmic, experimental, prototyping and implementation; Big Data Algorithms, Applications and Services; Big Data Mining and Analytics; Big Data Processing and Querying; Cloud and Big Data for Internet of Things (IoT); Computing, scheduling and resource management for sustainability; Government and Industrial Experiences for Cloud and Big Data; Green Computing and Networking Technologies for Cloud and Big Data;

6th International Conference on Cloud, Big Data and Web Services (CBW 2025) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and Web services. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and web services. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to

Tel.: [8932587139];     Email: cbw@icaita2025.org

• 5G and Networks for Big Data • Big Data • Big Data Analytics and Social Media • Big Data Applications, Bioinformatics, Multimedia etc • Big Data Infrastructure and platform • Big Data Management • Big Data Mining • Big Data Search and Mining • Big Data Security, Privacy and Trust • Big Data Techniques, models and algorithms • Big Data Tools and systems • Business Service Systems Theory and Models • Case Studies and Theories in Cloud Computing • Cloud and grid computing for Big Data • Cloud Application, Infrastructure and Platforms • Cloud Applications in Vertical Industries • Cloud Based, Parallel Processing • Cloud Business • Cloud Computing • Cloud Storage and File Systems • Cluster, Grid, Utility and Cloud Computing Models and Systems • Consolidation NoSQL Data Stores • Data storage and Management in Cloud Computing • Design Tool for Cloud Computing • Empirical Studies on Web Service Computing • Energy Management and Programming Environments • Evaluation and Quality Models of Web Service Computing • Knowledge and Semantic Approaches Web and Business Service Domains • Location Based Services, Presence, Availability, and Locality • Machine Learning and AI for Big Data • Maintenance and Management of Cloud Computing Cloud Computing Architecture • Mobile Clouds for New Millennium, Mobile Devices • Networks within Cloud systems, the Storage Area, and to the Outside Virtualization in the Context of Cloud Computing • Other Related Topics • Performance, SLA Management and Enforcement • Platforms • Qualitative and Quantitative Studies and Analysis on Web Service Systems • Resource Provisioning • Security Techniques for the Cloud • Service Oriented Architecture Models and Systems • Service-Oriented Architecture in Cloud Computing • Simulations and Developments of Web Service Computing Systems • Social Clouds (Social Networks in the Cloud) • System Integration, Virtual Compute Clusters • The Open Cloud: Cloud Computing and Open Source • Tools and Technologies for Web Service Computing • Uncertainty Issues and Studies in Web Service Practices and Systems • Virtualization on Platforms in the Cloud • Web and Business Information Services and Systems • Web Service Computing Metrics and Standards • Web Service Computing Theory and Models • Web Service Domain Specific Case Studies and Application Systems • Web Services

TECHSPO Nashville

TECHSPO Nashville Technology Expo - May 19-20, 2025 - Nashville, TN

TECHSPO Nashville;     Tel.: [8008055385];     Email: events@techsponashville.com

entwickler.de Akademie | Software & Support Media GmbH

In unserem 2-tägigen IT Security Camp mit Christian Schneider erhalten Sie nicht nur tiefgehendes Wissen über Angriffstechniken & Sicherheitsmaßnahmen, sondern auch die praktischen Fähigkeiten, um IT-Risiken zu identifizieren und geeignete Gegenmaßnahmen zu implementieren – exakt das, was NIS-2 fordert.

entwickler.de Akademie;     Email: info@entwickler-akademie.de

Risikoanalysen, Schwachstellenmanagement, Sicherheitsmaßnahmen, Softwareentwicklung, IT-Infrastruktur, IT Sicherheit, IT-Security

Softwareentwicklung,    Informationssicherheit und Datenschutz

Sichuan Province Computer Federation

2025 The 8th International Conference on Artificial Intelligence and Big Data (ICAIBD 2025) will take place on May 23-26, 2025 in Chengdu, China. It is sponsored by Sichuan Province Computer Federation and technically assisted by many local and international universities. This conference provides you opportunity to meet with academicians as well as practitioners in the fields of Artificial Intelligence and Big Data from all over the world, and get the latest insights from every area of Artificial Intelligence and Big Data theory and practice. ICAIBD features invited keynote speech, peer-reviewed paper presentations, and academic visit. The conference is completely open (one needs to register first), you will not have to be an author or a discussant to attend. Submissions will be peer-reviewed and evaluated based on originality, relevance to conference, contributions, and presentation. We invite the submission of original research contributions.

Tel.: [86-28-87777577];     Email: emmaawang2019@sina.com

Artificial Intelligence Intelligent information systems Intelligent data mining and farming Intelligent web-based business Intelligent agents Intelligent networks Intelligent databases Intelligent user interface AI and evolutionary algorithms Intelligent tutoring systems Reasoning strategies Distributed AI algorithms and techniques Distributed AI systems and architectures Neural networks and applications Heuristic searching methods Languages and programming techniques for AI Constraint-based reasoning and constraint programming Intelligent information fusion Learning and adaptive sensor fusion Search and meta-heuristics Multisensor data fusion using neural and fuzzy techniques Integration of AI with other technologies Evaluation of AI tools Social intelligence (markets and computational societies) Social impact of AI Emerging technologies Brain models, Brain mapping, Cognitive science Natural language processing Fuzzy logic and soft computing Software tools for AI Decision support systems Automated problem solving Big Data Models and Algorithms Foundational Models for Big Data Algorithms and Programming Techniques for Big Data Processing Big Data Analytics and Metrics Representation Formats for Multimedia Big Data Big Data Architectures Cloud Computing Techniques for Big Data Big Data as a Service Big Data Open Platforms Big Data in Mobile and Pervasive Computing Big Data Management Big Data Persistence and Preservation Big Data Quality and Provenance Control Management Issues of Social Network Big Data Big Data Protection, Integrity and Privacy Models and Languages for Big Data Protection Privacy Preserving Big Data Analytics Big Data Encryption Big Data Search and Mining Algorithms and Systems for Big Data Search Distributed, and Peer-to-peer Search Machine learning based on Big Data Visualization Analytics for Big Data Big Data for Enterprise, Government and Society Big Data Economics Big Data for Business Model Innovation Big Data Toolkits Big Data in Business Performance Management SME-centric Big Data Analytics

Fuzhou University, China.

2025 3rd International Conference on Big Data and Privacy Computing will be held in Fuzhou, China during May 30-June 1, 2025. The event is sponsored by Fuzhou University, China. This conference provides opportunities for the different areas Delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. We hope that the conference results constituted significant contribution to the knowledge in these up-to-date scientific field.

Email: saraxc17@163.com

# # Track 1 - Big Data Architecture and Systems Big Data Algorithms, Applications and Services Structured and Unstructured Data/Text/Web Mining Big Data Architectures Algorithms and Systems for Big Data Search Big Data Analysis Analytics and Metrics Big Data Analysis Architectures Big Data Open Platforms Big Data Quality and Provenance Control Big Data Toolkits Foundational Models for Big Data Experiences with Big Data Project Deployments Hardware/software infrastructure for big data Techniques, models and algorithms for big data Tools and systems for big data Algorithms and Programming Techniques for Big Data Processing Big Data Analytics and Metrics # # Track 2 -Data Encryption and Privacy Protection Hardware and Software solutions for Big Data Searching, Storing and Management Privacy and Security for Cloud and Big Data Virtualization Technologies, Cloud Data Management and Storage, Cloud Resource Management and QoS Big Data Analysis Encryption Big Data Analysis Management Big Data as a Service Big Data Encryption Big Data in Business Performance Management Big Data in Enterprise Management Models and Practices Big Data in Government Management Models and Practices Collaborative Threat Detection using Big Data Analysis Analytics Management Issues of Social Network Big Data Models and Languages for Big Data Protection Privacy Preserving Big Data Analytics Security and privacy for big data Big Data Management Big Data Protection, Integrity and Privacy Security Applications of Big Data Anomaly Detection in Very Large Scale Systems Big Data Persistence and Preservation Data quality issues: such as validation, metrics, optimizations and consistency # # Track 3 - Big Data Analysis and Computing Big Data Mining and Analytics Big Data Processing and Querying Data Visualization and Visual Analytics Evolutionary and Bio-inspired approaches for Big Data analysis Big Data Visualization Machine learning based on Big Data Data-driven innovation, computational modelling and data integration Data intensive computing theorems and technologies Big Data Analysis Search and Mining Big data analytics and social media Data mining, graph mining and data science Intelligent Data Processing Visualization Analytics for Big Data Big Data Models and Algorithms Cloud Computing Techniques for Big Data Big Data in Mobile and Pervasive Computing Big Data Search and Mining Novel Computational Intelligence approaches for data analysis # # Track 4 - Big Data Science and Applications Representation Formats for Multimedia Big Data New domains and novel applications related to Big Data technologies Scientific Applications of Big Data Scalable computational intelligence tools Cloud and Big Data for Internet of Things (IoT) Government and Industrial Experiences for Cloud and Big Data Green Computing and Networking Technologies for Cloud and Big Data Big Data Education Big Data Analysis for Business Model Innovation Big Data Analysis for Enterprise, Government and Society Big Data Analysis Economics Big data applications: Bioinformatics Big Data for Business Model Innovation Big Data for Enterprise Transformation Big Data for Vertical Industries (including Government, Healthcare, and Environment) Big Data in Smart Planet Solutions Machine learning and AI for big data Real-life Case Studies of Value Creation through Big Data Analytics SME-centric Big Data Analytics Software Engineering for Cloud Computing and Big Data Software, hardware and algorithm co-design, high-performance computing Software and tools for big data management # # Track 5 - Data Security and Blockchain Application Technology Blockchain Blockchain based lightweight data structures for IoT data Blockchain based IoT security solutions Blockchain in cyber physical systems Blockchain in social networking Bolckchain in crowdsourcing and crowdsensing Blockchain in 5G Blockchain in edge and cloud computing Blockchain and trust management Cryptocurrency Cryptographic hash function Cryptography Distributed ledger Distributed consensus algorithm Blockchain for business Blockchain for industries Blockchain for Cryptocurrency security Blockchain for supply chain solutions

MIPRO Croatian Society

The term Business intelligence (BI) refers to applications and technologies used to gather, provide access to, and analyze data and information about company operations in order to help them to have a more comprehensive knowledge of the factors affecting their business. BI systems usually lean on data warehouses (DWs) to guarantee an easy and quick access to information. More than twenty years of research in the data warehousing field paved the way for new applications that goes beyond traditional OLAP analysis and concern real-time, spatiotemporal as well as distributed data. Furthermore, BI research is now dealing with the integration of BI with Corporate Performance Management (CPM), Business Process Management (BPM), Social Business Intelligence, Semantic Web, and Big Data Processing.

Boris Vrdoljak - conference chair;     Tel.: [+38551423984];     Email: boris.vrdoljak@fer.hr

Data Warehouse and OLAP Business Intelligence Big Data Analytics - Algorithms, Techniques, Systems, User Interfaces Big Data Processing Big Data Analytics Applications in Science, Healthcare, Telecommunication, e-Business, etc., Data Science – Methods for Analyzing Scientific Data, Data Mining, Predictive and Descriptive Analytics and its Application in Science, Education, Healthcare, Telecommunications, Energy Providing, etc., Analytics for the Cloud Infrastructure, Social Network Analysis (SNA), CRM (Customer Relationship Management) and Social CRM, Analytics for Data Streams and Sensor Data, Edge Analytics, Analytics for Temporal, Spatial, Spatio-temporal and Mobile Data, Text, Web and Sentiment Analysis, Semantic Web and Semantic Data Integration, Education Management Information Systems, Business Information Systems, ERP and Supply Chain Management, Business Systems Integration, Business Process Management (BPM), Integration of Digital Twin and Big Data Technology

CZESND

2025 9th International Conference on Power Energy Systems and Applications (ICoPESA) will be held at Nanjing, China during June 20-22, 2025. ICoPESA 2025 is sponsored by Nanjing University of Aeronautics and Astronautics. The conference continues to retain its tradition of high-quality conference and will open up an opportunity for academics and industrial professionals worldwide to exchange their knowledge of the state-of-the-art power energy systems and applications, the future role of power energy systems in ecological revolution will be explored at ICoPESA.

Email: Nazal@sina.com

Power system solutions towards a net-zero future; Energy efficiency and low carbon emission; Big data & AI in energy internet; New-type power system; Power electronics application in power systems; Aerospace power electronics; Renewable energy and energy storage systems; Electric power sustainable technologies; Transportation electrification and more-electric-aircraft; Power equipment planning & asset management;

Stromversorgungsnetz, Intelligentes Stromnetz,    Systemtheorie, Regelung und Automatisierung

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This summer school is an intensive course on software techniques for data management and database management. Topics include database command translation and query optimization, query execution and indexing, row- and column-oriented storage structures and algorithms, optimistic and pessimistic concurrency control, logging and recovery, replication and high availability, scalability and cloud computing, and more. The goal of lectures and presentations is to understand classic techniques and to link them to industrial reality and to research opportunities. The target audience are recent MS graduates who have already taken 2-3 courses covering data management software and who are embarking on a career in industrial development or in academic research in related topics.

Veranstaltungen für Studenten der Informatik,    Datenbanktechlologie, Suchmaschinen und Data-Mining

entwickler.de Akademie | Software & Support Media GmbH

In unserem 2-tägigen IT Security Camp mit Christian Schneider erhalten Sie nicht nur tiefgehendes Wissen über Angriffstechniken & Sicherheitsmaßnahmen, sondern auch die praktischen Fähigkeiten, um IT-Risiken zu identifizieren und geeignete Gegenmaßnahmen zu implementieren – exakt das, was NIS-2 fordert.

entwickler.de Akademie;     Email: info@entwickler-akademie.de

Risikoanalysen, Schwachstellenmanagement, Angriffstechniken, Sicherheitsmaßnahmen, Softwareentwicklung, IT-Infrastruktur, Security Schwachstellen, Web-Security-Schwachstellen, Angriffsszenarien, Trainingsanwendung, DEVSECOPS, CI/CD-PIPELINES

Softwareentwicklung,    Informationssicherheit und Datenschutz

Henry Stewart Events

Email: simid@henrystewart.co.uk

Semantic Data, Semantic Layer, Linked Data, knowledge graph, semantic architect, NLP, natural language processing, semantic analysis, semantic taxonomy, taxonomies, ontology, ontologies, knowledge graphs, semantic web, RDF, Resource Description Framework, OWL, Ontology Web Language, Ontology, Ontologies, Semantic Technology, SPARQL, Interoperability, Information Science, Artificial Intelligence, Data Integration, Semantic Web, Semantic Engineering, MLIS, Masters in Library Science

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

The Autumn School for Information Retrieval and Information Foraging (ASIRF) focuses on recent developments in Information Retrieval and Information-Seeking behavior and their applications. Information Retrieval deals with searching in huge amounts of unstructured data. In many professional fields of work and everyday life, access to text data via search engines is one of the most important forms of access to knowledge. Information Foraging aims to model the entire process from the awareness of an information problem through selecting appropriate information sources to the actual search.

Students and lecturers will live together for a week at Schloss Dagstuhl, which guarantees the school's traditionally highly communicative and interactive atmosphere. The intended audience of ASIRF are doctoral students and young researchers working in Information Retrieval, Information Foraging, or using concepts or methods from these fields in their research

Veranstaltungen für Studenten der Informatik,    Datenbanktechlologie, Suchmaschinen und Data-Mining

University of Catania, Italy & University of Florida, USA

LOD 2025, An Interdisciplinary Conference: Deep Learning, Foundation Models & Artificial Intelligence without Borders

Event Secretariat;     Email: lod@icas.cc

Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data, Optimization, Generative AI, Foundation Models, Large Language Models

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Verarbeitung Natürlicher Sprache, Computerlinguistik

Henry Stewart Events

Following the success of the inaugural event, Semantic Data New York returns in 2025, bringing together leading practitioners and innovators to explore the latest advancements in data management, taxonomy, ontology, and knowledge graph development. We are delighted to welcome back Madi Weland Solomon, Head of Client Solutions at Graphifi, as conference chair for this year’s event. Join us for a one-day conference exploring the critical role of data in shaping business advantage in the AI era. Gain practical insights into effectively managing and leveraging data resources, with a strong focus on taxonomies, ontologies, and knowledge graphs.

Email: simid@henrystewart.co.uk

Semantic Data, Semantic Layer, Linked Data, knowledge graph, semantic architect, NLP, natural language processing, semantic analysis, semantic taxonomy, taxonomies, ontology, ontologies, Ontologist, knowledge graphs, semantic web, RDF, Resource Description Framework, OWL, Ontology Web Language, Ontology, Ontologies, Semantic Technology, SPARQL, Interoperability, Information Science, Artificial Intelligence, Data Integration, Semantic Web, Taxonomies, Taxonomist

York College, City University of New York

We are pleased to warmly invite you to the International Conference On Business, Management, Economics, and Information Systems - 2025 (ICBMEIS-2025), organized by the Department of Business and Economics, York College, City University of New York (CUNY), Jamaica, New York, United States. ICBMEIS - 2025 is scheduled for October 25-26, 2025, at the Department of Business and Economics. ICBMEIS - 2025‎ is dedicated to fostering the exchange of knowledge, innovative ideas, and discussions on the latest advancements in the fields of Business, Management, Economics, and Information Systems. This conference will provide a valuable platform for esteemed academicians, scholars, and researchers to connect, collaborate, and interact with peers from both national and international arenas.

Conference Secretariat;     Email: icbm@york.cuny.edu

Business, Management, Entrepreneurship, Supply Chain Management, Operations Management, Human Resource Management, Marketing, Information Systems, Economics, Data Analytics, Engineering & Technology, Accounting and Finance, Sustainability, Aviation Management

Wirtschaftswissenschaft, Unternehmen und Marketing,    Berufliche Laufbahn und Management

entwickler.de Akademie | Software & Support Media GmbH

Die Teilnehmenden lernen hier Wege zur Realisierung dynamischer Cloud-Native-Architekturen, Container Application Design, Logging/Monitoring/Alerting, Container Native Storage und Möglichkeiten zur UI-Integration. Ebenso werden typische Konzepte aktueller Container-Manager aufgezeigt und vermittelt, wie sich damit für größere Webanwendungen gängige Qualitätsanforderungen realisieren lassen. Zusätzlich werden bekannte Cloud-Anbieter klassifiziert, Möglichkeiten zur Automatisierung aufgezeigt, Ansätze der Softwareentwicklung und des Application Lifecycle besprochen.

entwickler.de Akademie;     Email: info@entwickler-akademie.de

Infrastruktur, Container und Cloud Native, iSAQB, Schulung, Trainer, Fortbildung, Weiterbildung, Software-Architecture, Camp, Advanced, Credits, loud-Native-Architekturen, Container Application Design, Logging/Monitoring/Alerting, Container Native Storage, UI-Integration

Edge/Cloud-Computing,    Eingebettete Systeme, RFIDs

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

More and more, we find that the provenance of data is a key missing ingredient in the information set made available to us. Provenance - the origination and intention of data as collected - provides significant challenges for modern networks. While standards exist for describing data and its analysis - and even for parts of the provenance chain - there is no standard mechanism for tying together all relevant information across the series of steps which fully describe the origination of data. This workshop explores how the many contextualising factors needed to support responsible and accurate data reuse can be described, allowing for the needed chaining of provenance steps.

SEIT Lab, Department of Computer Science, University of Cyprus

The annual IEEE International Conference on Knowledge Graph (ICKG) provides a premier

international forum for presentation of original research results in knowledge discovery and

graph learning, discussion of opportunities and challenges, as well as exchange and

dissemination of innovative, practical development experiences. The conference covers all

aspects of knowledge discovery from data, with a strong focus on graph learning and

knowledge graph, including algorithms, software, platforms. ICKG 2025 intends to draw

researchers and application developers from a wide range of areas such as knowledge

engineering, representation learning, big data analytics, statistics, machine learning, pattern

recognition, data mining, knowledge visualization, high performance computing, and World

Wide Web etc. By promoting novel, high quality research findings, and innovative solutions to

address challenges in handling all aspects of learning from data with dependency relationship.

All accepted papers will be published in the conference proceedings by the IEEE Computer

Society. Awards, including Best Paper, Best Paper Runner up, Best Student Paper, Best Student

Paper Runner up, will be conferred at the conference, with a check and a certificate for each

award. The conference also features a survey track to accept survey papers reviewing recent

studies in all aspects of knowledge discovery and graph learning. At least five high quality

papers will be invited for a special issue of the Knowledge and Information Systems Journal,

in an expanded and revised form. In addition, at least eight quality papers will be invited for a

special issue of Data Intelligence Journal in an expanded and revised form with at least 30%

difference.

Tel.: [00357722892693];     Email: george@ucy.ac.cy

• Foundations, algorithms, models, and theory of knowledge discovery and graph learning • Knowledge engineering with big data. • Machine learning, data mining, and statistical methods for data science and engineering. • Acquisition, representation and evolution of fragmented knowledge. • Fragmented knowledge modeling and online learning. • Knowledge graphs and knowledge maps. • Graph learning security, privacy, fairness, and trust. • Interpretation, rule, and relationship discovery in graph learning. • Geospatial and temporal knowledge discovery and graph learning. • Ontologies and reasoning. • Topology and fusion on fragmented knowledge. • Visualization, personalization, and recommendation of Knowledge Graph navigation and interaction. • Knowledge Graph systems and platforms, and their efficiency, scalability, and privacy. • Applications and services of knowledge discovery and graph learning in all domains including web, medicine, education, healthcare, and business. • Big knowledge systems and applications. • Crowdsourcing, deep learning and edge computing for graph mining. • Large language models and applications • Open source platforms and systems supporting knowledge and graph learning. • Datasets and benchmarks for graphs • Neurosymbolic & Hybrid AI systems • Graph Retrieval Augmented Generation