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Record W1592536978 · doi:10.15353/joci.v9i3.3161

Museums as Living Labs Challenge, Fad or Opportunity?

2013· article· en· W1592536978 on OpenAlexvenueno aff
Mariana Salgado

Bibliographic record

VenueThe Journal of Community Informatics · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsLiving labWork (physics)Public relationsInformation and Communications TechnologyProcess (computing)Cultural heritageSociologyComputer scienceWorld Wide WebPolitical scienceEngineering

Abstract

fetched live from OpenAlex

On the basis of case studies in Finland, this paper describes and analyzes how the museum community has designed, integrated and implemented ICT in its organizations. The museum community has participated in the development of a conceptual framework for ICT services as well as the resources required to put them to use. Due to the similarity between this sort of work and the tasks performed at living labs, I believe that museums could benefit from dialoguing with living labs about their methods, networks and new technologies, indeed their entire ecosystems. Living labs include the public, private and civil sectors as key actors as they generate and test new products and services. They are spaces of innovation that engage these actors at the different phases of development. But most importantly, the use of living labs’ user-centered design methods is becoming much more widespread. Museums create and use products and services to further their mission of conserving, researching and communicating our common cultural heritage. This paper addresses how museums can make use of and benefit from living labs in their attempts to open their institutions to new audiences and enhance audience participation. This paper also discusses how communities can actively participate in the creation of museum programs and activities. The existing literature (Eriksson, Niitamo, Kulkki & Hribernik, 2006, Eskola, 2011) describes the work carried out at living labs and contrasts it with work done in museums in Helsinki where interactive pieces have been produced and implemented through a co-design process involving external collaborators, audience and museum staff. My hypothesis is that if cultural institutions like museums, exhibition halls, libraries and cultural centers acted like living labs, or took part in their activities, they could begin a dialogue with other strategic partners, including an array of research units, and the civil and private sectors. Rather than fostering innovation in their own spaces and based on their audiences’ needs, museums currently use technological solutions designed for other contexts, adapting theme to fit their needs. By changing the way that museums refer to themselves and their partnerships, it might be possible not only to shed light on possible collaboration strategies but also to review the role of museums in society and the future. Though the term “living lab” might be a fad, in the context of this publication it may help facilitate participation in and collaboration with the museum community. This paper also contrasts museums and living labs to highlight their common interest and possible points of convergence. As a result of my research, I believe that museums need to renovate in order to better incorporate ICTs with a user-centered design approach into their communities. User-centered design (UCD) is an approach and a process that heeds the needs, desires, and limitations of a product’s or service's end users at each stage of the design process. UCD has been widely applied due to its ability to help people appropriate and incorporate new technologies. UCD is a design philosophy and a process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.270
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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