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Ontology Engineering

Overview of attention for book
Cover of 'Ontology Engineering'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 General Terminology Induction in OWL
  3. Altmetric Badge
    Chapter 2 OBOWLMorph: Starting Ontology Development from PURO Background Models
  4. Altmetric Badge
    Chapter 3 A Similarity Based Approach to Omission Finding in Ontologies
  5. Altmetric Badge
    Chapter 4 An Ontology for Supporting the Evolution of Virtual Reality Scenarios
  6. Altmetric Badge
    Chapter 5 Collaborative Editing of Ontologies Using Fluent Editor and Ontorion
  7. Altmetric Badge
    Chapter 6 Integrating Ontology Negotiation and Agent Communication
  8. Altmetric Badge
    Chapter 7 Lifting EMMeT to OWL Getting the Most from SKOS
  9. Altmetric Badge
    Chapter 8 Experiences with Aber-OWL, an Ontology Repository with OWL EL Reasoning
  10. Altmetric Badge
    Chapter 9 Towards a Rule Based Distributed OWL Reasoning Framework
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    Chapter 10 Improving OWL RL Reasoning in N3 by Using Specialized Rules
  12. Altmetric Badge
    Chapter 11 On the Capabilities and Limitations of OWL Regarding Typecasting and Ontology Design Pattern Views
  13. Altmetric Badge
    Chapter 12 How to Keep a Reference Ontology Relevant to the Industry: A Case Study from the Smart Home
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    Chapter 13 An INSPIRE-Based Vocabulary for the Publication of Agricultural Linked Data
  15. Altmetric Badge
    Chapter 14 Towards a Core Ontology of Occupational Safety and Health
  16. Altmetric Badge
    Chapter 15 Towards a Visual Notation for OWL: A Brief Summary of VOWL
  17. Altmetric Badge
    Chapter 16 Snap-SPARQL: A Java Framework for Working with SPARQL and OWL
  18. Altmetric Badge
    Chapter 17 An Application Ontology to Help Users of a Geo-decision Software Understanding Their Data
  19. Altmetric Badge
    Chapter 18 Ontology Engineering: From an Art to a Craft
Attention for Chapter 5: Collaborative Editing of Ontologies Using Fluent Editor and Ontorion
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Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
10 Mendeley
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Chapter title
Collaborative Editing of Ontologies Using Fluent Editor and Ontorion
Chapter number 5
Book title
Ontology Engineering
Published in
Lecture notes in computer science, April 2016
DOI 10.1007/978-3-319-33245-1_5
Book ISBNs
978-3-31-933244-4, 978-3-31-933245-1
Authors

A. Seganti, P. Kapłański, P. Zarzycki

Editors

Valentina Tamma, Mauro Dragoni, Rafael Gonçalves, Agnieszka Ławrynowicz

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 30%
Student > Bachelor 2 20%
Student > Doctoral Student 2 20%
Unknown 3 30%
Readers by discipline Count As %
Computer Science 5 50%
Engineering 2 20%
Unknown 3 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2016.
All research outputs
#3,979,376
of 7,684,314 outputs
Outputs from Lecture notes in computer science
#3,278
of 6,471 outputs
Outputs of similar age
#145,550
of 267,935 outputs
Outputs of similar age from Lecture notes in computer science
#48
of 85 outputs
Altmetric has tracked 7,684,314 research outputs across all sources so far. This one is in the 28th percentile – i.e., 28% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,471 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,935 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.