Realising the affective potential of patents: a new model of database interpretation for user-centred design

Research output: Contribution to journalArticle

  • 1 Citations

Abstract

This research sets out a new interpretation of the patent database using affective design parameters. While this resource contains a vast quantity of technical information, its extraction and use in practical design settings is extremely challenging. Until now, all filing and subsequent landscaping or profiling of patents has been based on their technical characteristics. We set out an alternative approach that utilises crowdsourcing to first summarise patents and then applies text analysis tools to assess the summarising text in relation to three affective parameters: appearance, ease of use, and semantics. The results been used to create novel patent clusters that provide an alternative perspective on relevant technical data, and support user-centric engineering design. The workflow and tasks to effectively interface with the crowd are outlined, and the process for harvesting and processing responses using a combination of manual and computational analysis is reviewed. The process creates sets of descriptive words for each patent which differ significantly from those created using only functional requirements, and support a new paradigm for the use of big data in engineering design – one that utilises desirable affective qualities as the basis for scouring and presenting relevant functional patent information for concept generation and development.
LanguageEnglish
Pages484-511
Number of pages43
JournalJournal of Engineering Design
Volume29
Issue number8-9
Early online date8 Mar 2018
DOIs
StateE-pub ahead of print - 8 Mar 2018

Fingerprint

Semantics
User centered design
Processing
Big data

Keywords

  • patents
  • crowdsourcing
  • affective design

Cite this

@article{5e1bd6c7f96c4ece8d88c433ee814b52,
title = "Realising the affective potential of patents: a new model of database interpretation for user-centred design",
abstract = "This research sets out a new interpretation of the patent database using affective design parameters. While this resource contains a vast quantity of technical information, its extraction and use in practical design settings is extremely challenging. Until now, all filing and subsequent landscaping or profiling of patents has been based on their technical characteristics. We set out an alternative approach that utilises crowdsourcing to first summarise patents and then applies text analysis tools to assess the summarising text in relation to three affective parameters: appearance, ease of use, and semantics. The results been used to create novel patent clusters that provide an alternative perspective on relevant technical data, and support user-centric engineering design. The workflow and tasks to effectively interface with the crowd are outlined, and the process for harvesting and processing responses using a combination of manual and computational analysis is reviewed. The process creates sets of descriptive words for each patent which differ significantly from those created using only functional requirements, and support a new paradigm for the use of big data in engineering design – one that utilises desirable affective qualities as the basis for scouring and presenting relevant functional patent information for concept generation and development.",
keywords = "patents, crowdsourcing, affective design",
author = "Andrew Wodehouse and Gokula Vasantha and Jonathan Corney and Ananda Jagadeesan and Ross Maclachlan",
year = "2018",
month = "3",
day = "8",
doi = "10.1080/09544828.2018.1448056",
language = "English",
volume = "29",
pages = "484--511",
journal = "Journal of Engineering Design",
issn = "0954-4828",
number = "8-9",

}

TY - JOUR

T1 - Realising the affective potential of patents

T2 - Journal of Engineering Design

AU - Wodehouse,Andrew

AU - Vasantha,Gokula

AU - Corney,Jonathan

AU - Jagadeesan,Ananda

AU - Maclachlan,Ross

PY - 2018/3/8

Y1 - 2018/3/8

N2 - This research sets out a new interpretation of the patent database using affective design parameters. While this resource contains a vast quantity of technical information, its extraction and use in practical design settings is extremely challenging. Until now, all filing and subsequent landscaping or profiling of patents has been based on their technical characteristics. We set out an alternative approach that utilises crowdsourcing to first summarise patents and then applies text analysis tools to assess the summarising text in relation to three affective parameters: appearance, ease of use, and semantics. The results been used to create novel patent clusters that provide an alternative perspective on relevant technical data, and support user-centric engineering design. The workflow and tasks to effectively interface with the crowd are outlined, and the process for harvesting and processing responses using a combination of manual and computational analysis is reviewed. The process creates sets of descriptive words for each patent which differ significantly from those created using only functional requirements, and support a new paradigm for the use of big data in engineering design – one that utilises desirable affective qualities as the basis for scouring and presenting relevant functional patent information for concept generation and development.

AB - This research sets out a new interpretation of the patent database using affective design parameters. While this resource contains a vast quantity of technical information, its extraction and use in practical design settings is extremely challenging. Until now, all filing and subsequent landscaping or profiling of patents has been based on their technical characteristics. We set out an alternative approach that utilises crowdsourcing to first summarise patents and then applies text analysis tools to assess the summarising text in relation to three affective parameters: appearance, ease of use, and semantics. The results been used to create novel patent clusters that provide an alternative perspective on relevant technical data, and support user-centric engineering design. The workflow and tasks to effectively interface with the crowd are outlined, and the process for harvesting and processing responses using a combination of manual and computational analysis is reviewed. The process creates sets of descriptive words for each patent which differ significantly from those created using only functional requirements, and support a new paradigm for the use of big data in engineering design – one that utilises desirable affective qualities as the basis for scouring and presenting relevant functional patent information for concept generation and development.

KW - patents

KW - crowdsourcing

KW - affective design

UR - https://www.tandfonline.com/toc/cjen20/current

U2 - 10.1080/09544828.2018.1448056

DO - 10.1080/09544828.2018.1448056

M3 - Article

VL - 29

SP - 484

EP - 511

JO - Journal of Engineering Design

JF - Journal of Engineering Design

SN - 0954-4828

IS - 8-9

ER -