Page - 50 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments
Image of the Page - 50 -
Text of the Page - 50 -
raw data; the data structures and storage, including correlated data; the dimension re-
duction issues; the need of visualizing all stages the extraction stages (particularly in
exploratory data analyses and conveying the results). Tohave positive results, it is nec-
essary to extract the relevant information and avoid the information not useful. For this
reason,we are applying some textmining techniques to identify and extract structured
representationsfromrawunstructureddatasources.This involvesanapproach tomining
documentswith semi-structured information and natural language, aswell as expertise
inmachine learningmodels for time-series, clustering, associations, and rule inference.
3.2. KnowledgeGraphs
Thekey idea is to explore thedata fromdifferent sources to extract knowledge that can
helppolicyauthorities and the tourist industry stakeholders tomakecitizen live smarter,
moresustainableandmoreaccessible. Inanutshell, thisdatawillbeacquired,processed
and modeled as a knowledge graph [8], resulting in a Knowledge Base in which the
entities are represented as nodeswhile contracts and their properties are represented as
edges. There are twomain reasons for the choice of this approach. On the one hand,
graphsareanatural representation for this typeofdata,whichwill facilitate thecreation
of context and the finding of relevant insights. On the other hand, it also constitutes a
naturalway for visualizing these data, very close to our abstractions, as opposed to tra-
ditional database tables. Thiswill allowcreating intuitive and rich graphical interfaces,
which evennon-technical userswill be able touse toperformdata query andvisualiza-
tion. TheKnowledgeBasewill also support the building ofmodels that not only bring
the patterns that are hidden in the data to light but also allow for the forecast of future
needs.
3.3. DataVisualization
The capability of supporting timely decisions based on visualizing big data is essential
tovariousdomains,namely tourism.This isessential foradecisionmaker tounderstand
not merely the events that occur in the specific location, but more importantly, where
theyoccur, that is, the spatialdistributionofevents.Weintend toapplyseveralpipelines
of data visualization techniques to our accumulated data. A tool is being developed to
create amachine-readable specificationof infographics, deployedusingopenstandards,
e.g., JSONandlinkeddata,andthatcanbeeasilysharedandlinkedtoothermedia.Also,
this toolallowsplottingourdatausingexploratorydataanalysis, suchashistograms,pie-
charts, and timeseries.On theotherhand,weareusingaweb-based interactivemethod-
ology, to visualize and understand the temporal dynamics of the datamore deeply. By
using statistical-learning analysis with geospatial analysis, applyingD3.js, and google
mapAPI libraries,weintendtoenhance theunderstandingofanaccessibleandinclusive
tourism-relateddata inbothabstract andgeographicalways.
4. Conclusions
Wepresentedkeychallengesandasolutionapproach,usingknowledgegraphs,dataanal-
ysis, andvisualization, forenablingaccessibleand inclusive tourismdecision-making in
aSmartCity context. Theproposed solution is tailored for both policy authorities, aca-
M.GomesandP.Novais /AData-DrivenTool toPromoteTourism
forPeoplewithDisabilities50
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Title
- Intelligent Environments 2019
- Subtitle
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Authors
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-Cía
- Publisher
- IOS Press BV
- Date
- 2019
- Language
- German
- License
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Size
- 16.0 x 24.0 cm
- Pages
- 416
- Category
- Tagungsbände