[CfP] Spatio-Temporal Data Management and Analysis for Knowledge Discovery Workshop - Rome - 8 November 2026

[Clement Iphar]

Call for Papers - STMA4KD Workshop 

Spatio-Temporal Data Management and Analysis
for Knowledge Discovery Workshop

 CIKM 2026 - Rome, Italy - November 8, 2026

https://gt-gast.irisa.fr/stm4kd/

Abstract: STMA4KD invites submissions on the management and analysis of spatial, temporal, and spatio-temporal data for knowledge discovery. The workshop will provide an international forum for researchers and practitioners in data management, knowledge discovery, information retrieval, machine learning, and application domains to exchange methods, systems, datasets, benchmarks, and emerging research questions. The program will combine peer-reviewed contributions with interactive presentations and discussion, and may include an invited talk or panel.

Organising Committee:

●   Clément Iphar, CRC / Mines Paris - PSL (Sophia Antipolis, France)

●   Aurélie Leborgne, ICube / University of Strasbourg (Strasbourg, France)

●   Nida Meddouri, LRE / EPITA (Paris, France)

●   Loïc Salmon, ISEA / University of New Caledonia (Nouméa, New Caledonia)

●    Juba Agoun, ERIC Research Unit / Université Lumière Lyon 2 (Lyon, France)

●      Assaad Zeghina, LATMOS (UVSQ / Sorbonne University) / Inria (Paris, France)

●    Nazha Selmaoui, ISEA / University of New Caledonia (Nouméa, New Caledonia)

Description: Spatial and temporal information has become a first-class concern in knowledge and information management. Data associated with time and location arise in web and open data, sensor infrastructures, multimodal analytics, document collections, mobility systems, Earth observation, environmental monitoring, healthcare trajectories, maritime intelligence, and public-sector platforms. STMA4KD adopts a broad view of such data: submissions may analyze explicitly georeferenced or timestamped data, or extract spatial and temporal knowledge from complex sources such as text, images, video, maps, and multimodal streams. Relevant challenges span acquisition, integration, representation, storage, querying, analysis, visualization, and dissemination in batch, streaming, centralized, distributed, or federated settings.Despite rapid advances in time-series analysis, trajectory mining, geo-temporal learning, and sensor analytics, research remains fragmented across domains. Many communities nevertheless face shared challenges, including heterogeneous data integration, scalability, uncertainty, privacy, data quality, explainability, robust evaluation, and reproducibility. STMA4KD is intended as a cross-disciplinary venue in which these common bottlenecks can be examined through methods, systems, resources, and applications.

Objectives: The workshop aims to bring together researchers and practitioners from academia, industry, and the public sector who address spatial and temporal information throughout the data lifecycle. It seeks to connect data management, knowledge discovery, information retrieval, machine learning, and application communities; encourage exchange between methodological and domain-driven research; identify reusable approaches, benchmarks, datasets, and evaluation protocols; and formulate shared research priorities and open problems. STMA4KD builds on the GAST workshop series while extending its scope to a broader international CIKM audience.

Workshop Topics (non-exhaustive list): We welcome contributions on needs, challenges, tools, techniques, methods, algorithms, systems, and resources involving:

• Temporal data: time series, sequences, event data, temporal graphs, longitudinal records, etc...
• Spatial data: geospatial databases, maps, remote-sensing imagery, geomatics, maritime data, etc.;
  
• Spatio-temporal data: trajectories, mobility traces, sensor networks, biological and medical data, moving objects, video, satellite image sequences, territorial data, etc.;
  
• Textual and multimodal sources containing or implying spatial and temporal information;
  
• Streaming and real-time data with spatial and/or temporal dimensions;
  
• Federated, privacy-sensitive, or geographically distributed spatial and temporal data.
  

The following research questions and topics are particularly welcome:

• Data acquisition, cleaning, quality assessment, integration, and provenance for spatial and temporal data;
  
• Modeling, representation, indexing, querying, storage, and scalable management of spatial, temporal, and spatio-temporal information;
  
• Heterogeneous, multidimensional, multiscale, multimodal, and semantic geo-temporal data integration;
  
• Machine learning, deep learning, graph-based learning, symbolic AI, and hybrid methods for spatial and temporal data;
  
• Pattern, rule, sequence, trajectory, and event discovery, including classification, prediction, clustering, and anomaly detection;
  
• Streaming analytics and real-time processing for trajectories, sensors, and event data;
  
• Uncertainty-aware, robust, and quality-conscious analysis and management;
  
• Privacy, anonymity, security, federated learning, and distributed processing for geographically dispersed data;
  
• Explainability, interpretability, visualization, and human-centered interaction for spatial and temporal models;
  
• Benchmarks, datasets, evaluation protocols, reproducibility, open science, and shared resources.
  

Contributions may address these questions conceptually, methodologically, systemically, or through applications in transportation and mobility, Earth observation, environmental monitoring, maritime systems, healthcare, public safety, digital humanities, industry, and the public sector. Methods, models, tools, datasets, and evaluation frameworks that transfer across application domains are particularly encouraged. 

Important Dates (all deadlines are at 11:59 PM AoE):

- Paper submission deadline: August 24, 2026

- Notification of acceptance: September 23, 2026

- Workshop: November 8, 2026

Instructions for Authors: Authors are invited to submit original work that has not been previously published and is not simultaneously under review elsewhere. Three submission formats are accepted: poster/extended abstracts of up to 2 pages; short papers of up to 4-6 pages; and full papers of 8-10 pages. Full papers should report mature methodological, system, or applied contributions. Short papers may present work in progress, datasets, benchmark proposals, reproducibility studies, or focused empirical findings. Poster/extended abstracts may describe emerging ideas, early-stage results, systems, or industry use cases.

Submissions must be written in English, prepared in PDF using the ACM two-column "sigconf" proceedings template (https://www.acm.org/publications/proceedings-template).

Submission: All submissions must be submitted electronically through the Microsoft CMT platform following this link: https://cmt3.research.microsoft.com/STMAKD2026/ 

Workshop papers will not be included in the ACM conference proceedings. We will publish proceedings for our workshop.

Each submission will receive at least two reviews. The evaluation criteria are:

• Relevance of the scientific content to the scope and themes of STMA4KD;
  
• Originality, significance, and potential impact of the contribution;
  
• Scientific and technical quality, including methodological soundness and appropriate evaluation;
  
• Clarity of presentation and accessibility to a multidisciplinary audience;
  
• Potential to stimulate constructive scientific discussion and contribute to shared research priorities.
  

At least one author of each accepted contribution must register for CIKM 2026 and present the work on site in Rome, Italy. Registration fees and procedures will be available on the CIKM 2026 website: https://cikm2026.diag.uniroma1.it/.

Acknowledgement : 

"The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support." 

Contact: clemen...@minesparis.psl.eu and nida.m...@epita.fr