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Chisel: Sculpting Tabular and Non-Tabular Data on the Web

Authors:

Johannes Doleschal,

Nico Höllerich,

Wim Martens,

Frank NevenAuthors Info & Claims

WWW '18: Companion Proceedings of the The Web Conference 2018

Pages 139 - 142

https://doi.org/10.1145/3184558.3186963

Published: 23 April 2018 Publication History

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Abstract

Chisel is a tool for flexible manipulation of CSV-like data, motivated by the recent effort of the World Wide Web Consortium (W3C) towards a recommendation for tabular data and metadata on the Web. In brief, Chisel supports an expressive built-in schema language for CSV-like data, that can handle both tabular and non-tabular data. Furthermore, it supports a simple programming language for transforming tabular and non-tabular CSV-like data. In the demo, we showcase the system for specifying and validating schemas, building transformations, and setting up a pipeline for automatic conversion of "wild" CSV-like data into structured tabular data. We present use cases for Chisel specifically targeted at exemplifying the ease of specifying, modifying, and understanding Sculpt schemas as well as extracting and transforming data.

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Cited By

View all

Liu DCheng PZhu HTang XChen YWang XPan WMing ZHe X(2023)DIWIFT: Discovering Instance-wise Influential Features for Tabular DataProceedings of the ACM Web Conference 202310.1145/3543507.3583382(1673-1682)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583382

Index Terms

Chisel: Sculpting Tabular and Non-Tabular Data on the Web
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Data model extensions
        Semi-structured data
  2. World Wide Web
    1. Web mining
      1. Data extraction and integration

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Information & Contributors

Information

Published In

WWW '18: Companion Proceedings of the The Web Conference 2018

April 2018

2023 pages

ISBN:9781450356404

General Chairs:
Pierre-Antoine Champin
Université Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, CNRS, LIRIS, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 23 April 2018

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Demonstration

Funding Sources

Special Research Fund (BOF) of Hasselt University
Deutsche Forschungsgemeinschaft (DFG)

Conference

WWW '18

Sponsor:

IW3C2

WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all

Liu DCheng PZhu HTang XChen YWang XPan WMing ZHe X(2023)DIWIFT: Discovering Instance-wise Influential Features for Tabular DataProceedings of the ACM Web Conference 202310.1145/3543507.3583382(1673-1682)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583382

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SCULPT: A Schema Language for Tabular Data on the Web

BonXai: Combining the Simplicity of DTD with the Expressiveness of XML Schema

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