France

Following the principles of linked data, billions of RDF data have been produced and hundreds of interconnected knowledge graphs are available through public SPARQL endpoints. However, existing SPARQL servers suffer from availability and scalability issues. In this talk, I will present the latest research results that address these issues. I will present approaches that balance the cost of query processing between data providers and data consumers in order to reduce the pressure on data providers. I will conclude my presentation with open research questions.

DATA 2021

Querying Decentralized Knowledge Graphs

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

The AAMAS conference series was initiated in 2002 in Bologna, Italy as a joint event comprising the 6th International Conference on Autonomous Agents (AA), the 5th International Conference on Multiagent Systems (ICMAS), and the 9th International Workshop on Agent Theories, Architectures, and Languages (ATAL).

Subsequent AAMAS conferences have been held in Melbourne, Australia (July 2003), New York City, NY, USA (July 2004), Utrecht, The Netherlands (July 2005), Hakodate, Japan (May 2006), Honolulu, Hawaii, USA (May 2007), Estoril, Portugal (May 2008), Budapest, Hungary (May 2009), Toronto, Canada (May 2010), Taipei, Taiwan (May 2011), Valencia, Spain (June 2012), Minnesota, USA (May 2013), Paris, France (May 2014), Istanbul, Turkey (May 2015), Singapore (May 2016), São Paulo (2017) and Stockholm, Sweden (2018), Montreal (May 2019), Auckland (May 2020, Virtual), London (May 2021, Virtual).

A ticket is required to attend this event, please register using the link below:

https://aamas2022-conference.auckland.ac.nz/attending/registration/

Registration Is Required

AAMAS 2022

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

keynote

The purpose of the International Conference on Data Science, Technology and Applications (DATA) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data. 
CONFERENCE AREAS 
1 . Business Analytics 
2 . Data Science 
3 . Data Management and Quality 
4 . Big Data 
5 . Databases and Data Security

The purpose of the International Conference on Data Science, Technology and Applications (DATA) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.


The role of information systems is changing in an increasingly digitalized world. Does this situation mean that established conceptual modeling practices relevant to the analysis and design of systems must change as well? In this talk, I will answer this question with a definite and affirmative “yes”. I will review the traditional assumptions around the conceptual modeling of information systems and demonstrate how advances in digital technology increasingly challenge these assumptions. I will then present a new framework for conceptual modeling that is consistent with the emerging requirements of a digital world. The framework draws attention to the role of conceptual models as mediators between physical and digital realities. It identifies new research questions about grammars, methods, scripts, agents, and contexts that are situated in intertwined physical and digital realities. I will discuss several implications for conceptual modeling scholarship for systems analysis and design that relate to the necessity of developing new methods and grammars for conceptual modeling, broadening the methodological array of conceptual modeling scholarship, and considering new dependent variables.

From Representation to Mediation: Modeling Information Systems in a Digital World

Multidimensional modeling, i.e., the design of cube schemata, has a key role in data warehouse (DW) projects, in self-service business intelligence, and in general to let users analyze data via the OLAP paradigm. Though an effective involvement of users in multidimensional modeling is crucial in these projects, not much has been said about how to establish a fruitful collaboration in projects involving numerous users with different skills, reputations, and degrees of authority. This issue is especially relevant in citizen science projects, where several volunteers can contribute their requirements despite not being formally-trained experts in the application domain. To fill this gap, we propose a framework for collaborative multidimensional modeling that can adapt itself to the pro-files and skills of the actors involved. We first classify users depending on their authoritativeness, skills, and engagement in the project. Then, following this classification, we identify four possible methodological scenarios and propose a profile-aware methodology supported by two sets of quality attributes. Finally, we describe a Group Decision Support System that implements our methodological framework and present some experiments carried out on a real case study.

A Profile-aware Methodological Framework for Collaborative Multidimensional Modeling: Agro-biodiversity Case Study

The global database research community has greatly impacted the functionality and performance of data storage and processing systems along the dimensions that define “big data”, i.e., volume, velocity, variety, and veracity. Locally, over the past five years, we have also been working on varying fronts. Among our contributions are: (1) establishing a vision for a database-inspired big data analytics system, which unifies the best of database and distributed systems technologies, and augments it with concepts drawn from compilers (e.g., iterations) and data stream processing, as well as (2) forming a community of researchers and institutions to create the Stratosphere platform to realize our vision. One major result from these activities was Apache Flink, an open-source big data analytics platform and its thriving global community of developers and production users. Although much progress has been made, when looking at the overall big data stack, a major challenge for database research community still remains. That is, how to maintain the ease-of-use despite the increasing heterogeneity and complexity of data analytics, involving specialized engines for various aspects of an end-to-end data analytics pipeline, including, among others, graph-based, linear algebra-based, and relational-based algorithms, and the underlying, increasingly heterogeneous hardware and computing infrastructure. At TU Berlin, DFKI, and the Berlin Institute for Foundations of Learning and Data (BIFOLD) we currently aim to advance research in this field via the Nebula Stream and Agora projects. Our goal is to remedy some of the heterogeneity challenges that hamper developer productivity and limit the use of data science technologies to just the privileged few, who are coveted experts. In this talk, we will outline how state-of-the-art SPEs have to change to exploit the new capabilities of the IoT and showcase how we tackle IoT challenges in our own system, NebulaStream. We will also present our vision for Agora, an asset ecosystem that provides the technical infrastructure for offering and using data and algorithms, as well as physical infrastructure components.

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Querying Decentralized Knowledge Graphs

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