Intro

The data management landscape has continued to rapidly diversify in the past few years. While the relational database (RDB) model continues to play a leading role, the challenges and opportunities evoked by modern data management call for new lines of thinking regarding models and computational solutions that go beyond traditional RDBs. Complex challenges for database research stem, in particular, from emerging requirements in machine learning, representations of uncertain data and knowledge, explainable AI, and data science in general.

The focus of the DBAI seminar will be on discussing these novel challenges – and the current and possible future approaches to address them – with the goal of identifying open questions and key opportunities for research at the intersection of data management and A.I.

Attending

The seminar is by invite only and will be held in Hotel Santa Cruz, November 12–15, 2019, in the Colchagua valley close to Santiago de Chile.

Accomodation in the hotel will be provided, as will transport to and from Santiago. Attendees are expected to fund other costs such as flights, accomodation before/after in Santiago, etc.

The city of Santa Cruz is 180 kms. and 2.5 hrs. by car south from Santiago. There will be buses leaving from downtown Santiago and Santiago airport to Santa Cruz on the morning of November 12, and going back to Santiago in the late afternoon of November 15. More logistic details will follow shortly.

Participants

  • Antoine Amarilli (Paris Telecom)
  • Renzo Angles (University of Talca)
  • Molham Aref (RelationalAI)
  • Marcelo Arenas (Pontificia Universidad Católica)
  • Eriq Augustine (UC Santa Cruz)
  • Pablo Barceló (Pontificia Universidad Católica)
  • Jorge Baier (Pontificia Universidad Católica)
  • Vaishak Belle (University of Edinburgh)
  • Christoph Berkholz (Humboldt University of Berlin)
  • Leo Bertossi (RelationalAI / Universidad Adolfo Ibáñez)
  • Meghyn Bienvenu (CNRS)
  • Peter Boncz (Vrije University)
  • Pierre Bourhis (University of Lille)
  • Carlos Buil Aranda (Universidad Técnica Federico Santa María)
  • Marco Calautti (University of Edinburgh)
  • Andrea Cali (Birbeck, University of London)
  • Diego Calvanese (Free University of Bozen-Bolzano)
  • David Carral (Dresden University)
  • Victor Dalmau (Universitat Pompeu Fabra)
  • Luc De Raedt (Katholieke Universiteit Leuven)
  • Diego Figueira (CNRS)
  • Marco Gaboardi (University of Buffalo)
  • Floris Geerts (Universiteit Antwerpen)
  • Lise Getoor (UC Santa Cruz)
  • Georg Gottlob (University of Oxford)
  • Martin Grohe (RWTH Aachen University)
  • Paolo Guagliardo (University of Edinburgh)
  • Claudio Gutierrez (University of Chile)
  • Olaf Hartig (Linköping University)
  • Aidan Hogan (University of Chile)
  • Alejandro Jara (Pontificia Universidad Católica)
  • Carlos Jerez (Universidad Adolfo Ibáñez)
  • Pavel Klinov (Stardog)
  • Christoph Koch (EPFL)
  • Paris Koutris (University of Maryland)
  • Laks Lakshmanan (University of British Columbia)
  • Leonid Libkin (University of Edinburgh)
  • Carsten Lutz (Universität Bremen)
  • Wim Martens (Universität Bayreuth)
  • Mikael Monet (University of Chile)
  • Marco Montali (Free University of Bozen-Bolzano)
  • Gonzalo Navarro (University of Chile)
  • Frank Neven (Hasselt University)
  • Hung Ngo (RelationalAI)
  • Milos Nikolic (University of Edinburgh)
  • Carlos Ochoa (University of Chile)
  • Federico Olmedo (University of Chile)
  • Rafael Peñaloza (University of Milano-Bicocca)
  • Reinhard Pichler (TU Vienna)
  • Andreas Pieris (University of Edinburgh)
  • Juan Reutter (Pontificia Universidad Católica)
  • Cristian Riveros (Pontificia Universidad Católica)
  • Andrea Rodríguez (University of Concepción)
  • Javiel Rojas (University of Chile)
  • Sudeepa Roy (Duke University)
  • Babak Salimi (University of Washington)
  • Emanuel Sallinger (TU Vienna)
  • Pierre Senellart (ENS)
  • Juan Sequeda (data.world)
  • Dan Suciu (University of Washington)
  • Eric Tanter (University of Chile)
  • Etienne Toussaint (University of Edinburgh)
  • Martín Ugarte (Pontificia Universidad Católica)
  • Guy Van den Broeck (University of California, Los Angeles)
  • Jan Van den Bussche (Hasselt University)
  • Domagoj Vrgoč (Pontificia Universidad Católica)

Agenda

Day 1: November 12
11:30–13:10 — Introduction
11:30–11:50 Welcome, Participant Introductions & Overview
11:50–12:10 Institute for Foundational Research on Data (IMFD) Pablo Barceló
12:10–12:30 Research at RelationalAI Molham Aref
12:30–12:50 The Data Observatory at UAI Carlos Jerez
12:50–13:10 Deep Reason Georg Gottlob
13:10–14:30 — Lunch
14:30–16:15 — Session 1: Structured Learning for Data Management and AI
14:30–15:15 Recent Advances and Challenges in Probabilistic (Logic) Programming Luc De Raedt
15:15–15:30 Expressive Power of Modern Neural Network Architectures Pablo Barceló
15:30–15:45 Missing Data and Machine Learning Guy Van den Broeck
15:45–16:00 Responsible Statistical Relational Learning Lise Getoor
16:00–16:15 Logic and Learning Victor Dalmau
16:15–16:45 — Coffee Break
16:45–18:30 — Session 2: Knowledge Representation
16:45–17:30 Efficient Query Evaluation under Rules Carsten Lutz
17:30–17:45 Reasoning in Data Science and Knowledge Graphs Emanuel Sallinger
17:45–18:00 Theoretical Aspects of Vadalog Georg Gottlob
18:00–18:15 Inconsistency Handling in Ontology-Mediated Query Answering Meghyn Bienvenu
18:15–18:30 Finite-Model Reasoning with Ontologies Andreas Pieris
Day 2: November 13
09:30–11:00 — Sessions 1 & 2: Discussion on Open Problems
11:00–11:30 — Coffee Break
11:30–13:00 — Sessions 1 & 2: Collaborative Work on Open Problems
13:00–14:30 — Lunch
14:30–16:15 — Session 3: Uncertainty in Data and Knowledge
14:30–15:15 Infinite Probabilistic Databases Martin Grohe
15:15–15:30 Explanations in Databases Sudeepa Roy
15:30–15:45 Fairness from a Data Management Perspective Babak Salimi
15:45–16:00 Probabilistic Ontologies Rafael Peñaloza
16:00–16:15 Query Lineages and Knowledge Compilation Antoine Amarilli
16:15–16:45 — Coffee Break
16:45–18:30 — Session 4: Graph Databases and Semistructured Data
16:45–17:30 G-CORE: A Core for Future Graph Query Languages Marcelo Arenas
17:30–17:45 Path Queries in Graph Databases Wim Martens
17:45–18:00 Path Queries in Stardog: Beyond SPARQL Property Paths Pavel Klinov
18:00–18:15 GraphQL from a Research Perspective Olaf Hartig
18:15–18:30 Schemas for Semistructured Data Juan Reutter
Day 3: November 14
09:30–11:00 — Sessions 3 & 4: Discussion on Open Problems
11:00–11:30 — Coffee Break
11:30–13:00 — Sessions 3 & 4: Collaborative Work on Open Problems
13:00–14:30 — Lunch
14:30–16:15 — Session 5: In-Database Optimisation of Query Languages
14:30–15:15 Relational Optimization Hung Ngo
15:15–15:30 Joins by Geometric Resolutions on Quadtrees Gonzalo Navarro
15:30–15:45 Estimating Correlated Joins Peter Boncz
15:45–16:00 Soft Constraints Dan Suciu
16:00–16:15 SQL + Linear Algebra = ? Floris Geerts
16:15–16:45 — Coffee Break
16:45–18:30 — Session 6: Privacy and Verification
16:45–17:30 Verification of Differential Privacy Marco Gaboardi
17:30–17:45 Verification and Reasoning for Process Mining Marco Montali
17:45–18:00 Verification of GraphQL Federico Olmedo
18:00–18:15 Reasoning on Leak of Information for Database Views Pierre Bourhis
18:15–18:30 Verification of Data-Aware Processes Diego Calvanese
Day 4: November 15
09:30–11:00 — Sessions 5 & 6: Discussion on Open Problems
11:00–11:30 — Coffee Break
11:30–13:00 — Sessions 5 & 6: Collaborative Work on Open Problems
13:00–14:30 — Lunch
14:30–16:15 — Conclusion / Wrap-up

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