Analysis of a Cultural Heritage Game with a Purpose with an Educational Incentive

Celino, Irene; Fiano, Andrea; Fino, Riccardo

doi:10.1007/978-3-319-38791-8_28

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…Indomilando 1 [6] is a web-based Game With a Purpose aimed to rank a quite heterogeneous set of images, depicting the cultural heritage assets of Milan. In each round the game shows the name of an asset and four photos, in which one represents the asset and the other three are put as distractors.…”

Section: Gwap For Link Ranking: Indomilandomentioning

confidence: 99%

“…In the tutorial, we provide some basic instruction and we explain how to embed the map by using Leaflet 6 , an open-source JavaScript library for mobilefriendly interactive maps. We do not detail the graphical aspect, letting developers define their desired look-and-feel to give the game a more personal flavour or mood.…”

Section: A Step-by-step Tutorial To Reuse the Frameworkmentioning

confidence: 99%

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A Framework to Build Games with a Purpose for Linked Data Refinement

Calegari¹,

Fiano²,

Celino³

2018

Lecture Notes in Computer Science

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With the rise of linked data and knowledge graphs, the need becomes compelling to find suitable solutions to increase the coverage and correctness of datasets, to add missing knowledge and to identify and remove errors. Several approaches -mostly relying on machine learning and NLP techniques -have been proposed to address this refinement goal; they usually need a partial gold standard, i.e. some "ground truth" to train automatic models. Gold standards are manually constructed, either by involving domain experts or by adopting crowdsourcing and human computation solutions. In this paper, we present an open source software framework to build Games with a Purpose for linked data refinement, i.e. web applications to crowdsource partial ground truth, by motivating user participation through fun incentive. We detail the impact of this new resource by explaining the specific data linking "purposes" supported by the framework (creation, ranking and validation of links) and by defining the respective crowdsourcing tasks to achieve those goals. To show this resource's versatility, we describe a set of diverse applications that we built on top of it; to demonstrate its reusability and extensibility potential, we provide references to detailed documentation, including an entire tutorial which in a few hours guides new adopters to customize and adapt the framework to a new use case.

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Section: Gwap For Link Ranking: Indomilandomentioning

confidence: 99%

Section: A Step-by-step Tutorial To Reuse the Frameworkmentioning

confidence: 99%

A Framework to Build Games with a Purpose for Linked Data Refinement

Calegari¹,

Fiano²,

Celino³

2018

Lecture Notes in Computer Science

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“…Addressing at scale the linked data refinement problem requires a trade-off between purely-manual and purely-automatic methods, with approaches that, on the one hand, adopt human computation [2] and crowdsourcing [3] to collect manually labeled training data and, on the other hand, employ statistical or machine learning to build models and apply the refinement operation on a larger scale. Indeed, active learning [4] and other recent research approaches in the artificial intelligence area have put back the "human-in-the-loop" by creating mixed human-machine approaches.…”

Section: Introductionmentioning

confidence: 99%

Refining Linked Data with Games with a Purpose

2020

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With the rise of linked data and knowledge graphs, the need becomes compelling to find suitable solutions to increase the coverage and correctness of data sets, to add missing knowledge and to identify and remove errors. Several approaches -mostly relying on machine learning and natural language processing techniques -have been proposed to address this refinement goal; they usually need a partial gold standard, i.e., some "ground truth" to train automatic models. Gold standards are manually constructed, either by involving domain experts or by adopting crowdsourcing and human computation solutions. In this paper, we present an open source software framework to build Games with a Purpose for linked data refinement, i.e., Web applications to crowdsource partial ground truth, by motivating user participation through fun incentive. We detail the impact of this new resource by explaining the specific data linking "purposes" supported by the framework (creation, ranking and validation of links) and by defining the respective crowdsourcing tasks to achieve those goals. We also introduce our approach for incremental truth inference over the contributions provided by players of Games with a Purpose (also abbreviated as GWAP): we motivate the need for such a method with the specificity of GWAP vs. traditional crowdsourcing; we explain and formalize the proposed process, explain its positive consequences and illustrate the results of an experimental comparison with stateof-the-art approaches. To show this resource's versatility, we describe a set of diverse applications that we built on top of it; to demonstrate its reusability and extensibility potential, we provide references to detailed documentation, including an entire tutorial which in a few hours guides new adopters to customize and adapt the framework to a new use case. C o r r e c t e d P r o o f Data Intelligence Refining Linked Data with Games with a Purpose

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Analysis of a Cultural Heritage Game with a Purpose with an Educational Incentive

Cited by 2 publications

References 17 publications

A Framework to Build Games with a Purpose for Linked Data Refinement

A Framework to Build Games with a Purpose for Linked Data Refinement

Refining Linked Data with Games with a Purpose

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