Publications related to Collaborative Schema Matching Reconciliation

Related publications (27)

E-Scan: Consuming Contextual Data with Model Plugins

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"

John Martin Kolinski, Lebohang Molefe

This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

Zenodo2023

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

Shared metadata for data-centric materials science

Giovanni Pizzi, Gian-Marco Rignanese

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

Nature Portfolio2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Melanie Nicole Zeilinger, Roland Schwan, Xuan Truong Nghiem

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Daniel Keller

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

2022

Quantitative assessment of research data management practice - 2021

Chiara Gabella, Francesco Varrato, Eliane Ninfa Blumer

This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried ou ...

2022

Data transformer apparatus

Christoph Koch, Babak Falsafi, Siddharth Gupta, Mark Johnathon Sutherland, Mario Paulo Drumond Lages De Oliveira, Arash Pourhabibi Zarandi, Zilu Tian, Hussein Kassir

Data transformer apparatus comprising at least a dispatcher module (D), a reader module (R), a converter module (C) and a writer module (W). The dispatcher module (D) is configured to: receive a data transformation request (DTR) including: a first informat ...

2021

An Integrated Approach to Learning Analytics

Denis Gillet, Juan Carlos Farah, Sandy Ingram

Despite the rise in services generating learning analytics, there is a lack of standard models and guidelines for data integration and aggregation to inform the design choices of applications supporting learning analytics. We propose a bottom-up, user-driv ...

2021

Data Management Plans: the Importance of Data Management in the BIG-MAP Project[**]

Nicola Marzari, Giovanni Pizzi, Martin Uhrin

Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a plan for the EU H2020 BIG-MAP proje ...

WILEY-V C H VERLAG GMBH2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Damien Bouffard, Camille Roland Marie Minaudo, Theo Baracchini

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters als ...

MDPI2021

Code Integration, Data Verification, and Models Validation Using the ITER Integrated Modeling and Analysis System (IMAS) in EUROfusion

Olivier Sauter, José Pedro Rebelo Ferreira Marques, Antoine Pierre Emmanuel Alexis Merle

The ITER Integrated Modelling and Analysis System (IMAS) has been adopted by the EUROfusion Consortium as a platform to facilitate the analysis and verification of data from multiple tokamaks for the integration of physics codes and the validation of physi ...

2020

Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges

François Maréchal

Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. T ...

2020

Graph Laplacian Mixture Model

Pascal Frossard, Hermina Petric Maretic

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in settings where all avai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

DELF: Safeguarding deletion correctness in Online Social Networks

Georgios Damaskinos

Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably oc ...

USENIX ASSOC2020

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Karl Aberer, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Zoltán Miklós

Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Reconciling Matching Networks of Conceptual Models

Karl Aberer, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Zoltán Miklós

Conceptual models such as database schemas, ontologies or process models have been established as a means for effective engineering of information systems. Yet, for complex systems, conceptual models are created by a variety of stakeholders, which calls fo ...

2019

A Method for Converting Current Data to RDF in the Era of Industry 4.0

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos, Damiano Nunzio Arena, Ioannis Tourkogiorgis, Marlène Hildebrand-Ehrhardt

In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Consolidation of database check constraints

Nikola Obrenovic

Independent modeling of various modules of an information system (IS), and consequently database subschemas, may result in formal or semantic conflicts between the modules being modeled. Such conflicts may cause collisions between the integrated database s ...

2019

A semantic-driven approach for Industry 4.0

Dimitrios Kyritsis, Gökan May, Sangje Cho

Toward industry 4.0, modern manufacturing companies are aiming at building digital twins to manage physical assets, processes, people, and places. Since in this environment, massive amounts of data have been generated and collected, integration and managem ...

IEEE2019