SMART: A tool for analyzing and reconciling schema matching networks

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists ...

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

Musical schemata constitute important structural building blocks used across historical styles and periods. They consist of two or more melodic lines that are combined to form specific successions of intervals. This paper tackles the problem of recognizing ...

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 ...

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 ...

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 ...

Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up. Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...

In this paper a hybrid framework is illustrated, with a software and hardware integration strategy, for an industrial platform that exploits features from a Relational Database (RDB) and Triplestore using the blackboard architectural pattern, ensuring effi ...

Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...

The major research in the resource management literature focuses primarily on two complementary sub-problems: (1) specification languages for formulating resource requests and (2) constraint problems modelling allocation and scheduling. Both directions ass ...

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...

Today, an ever-increasing number of researchers, businesses, and data scientists collect and analyze massive amounts of data in database systems. The database system needs to process the resulting highly concurrent analytical workloads by exploiting modern ...

We present an eye-tracking study in the context of Massive Open Online Course (MOOC) videos. We propose to use a pre-test as a way of priming students about the video content before they watch the video. In this study, we used two versions of the same pre- ...

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

As data collections become larger and larger, users are faced with increasing bottlenecks in their data analysis. More data means more time to prepare and to load the data into the database before executing the desired queries. Many applications already av ...

Schema matching is the process of establishing correspondences between the attributes of database schemas for data integration purposes. Although several automatic schema matching tools have been developed, their results are often incomplete or erroneous. ...

In this paper, an approach for information systems reverse engineering is proposed and applied. The aim is to support a unified perspective to the reverse engineering process of both data and software. At the state of the art, indeed, many methods, techniq ...

The common "one size does not fit all" paradigm isolates transactional and analytical workloads into separate, specialized database systems. Operational data is periodically replicated to a data warehouse for analytics. Competitiveness of enterprises today ...

Database systems deliver impressive performance for large classes of workloads as the result of decades of research into optimizing database engines. High performance, however, is achieved at the cost of versatility. In particular, database systems only op ...

SMART: A tool for analyzing and reconciling schema matching networks

Chat with Graph Search

Graph integration of structured, semistructured and unstructured data for data journalism

Micro-architectural Analysis of Database Workloads

Voice-leading Schema Recognition using Rhythm and Pitch Features

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

Consolidation of database check constraints

Reconciling Matching Networks of Conceptual Models

Timely and cost-efficient data exploration through adaptive tuning

A hybrid framework for industrial data storage and exploitation

Privacy - Preserving Data Exchange and Aggregation in Healthcare

Constraint-Flow Nets: A Model for Building Constraints from Resource Dependencies

Just-in-time Analytics Over Heterogeneous Data and Hardware

Scaling Up Concurrent Analytical Workloads on Multi-Core Servers

Shaping learners’ attention in Massive Open Online Courses

Toward timely, predictable and cost-effective data analytics

NoDB: Efficient Query Execution on Raw Data Files

Reconciling Schema Matching Networks Through Crowdsourcing

Pay-as-you-go Reconciliation in Schema Matching Networks

Pattern detection for conceptual schema recovery in data-intensive systems

Scaling up Mixed Workloads: a Battle of Data Freshness, Flexibility, and Scheduling

Adaptive Query Processing on RAW Data