Seite - 49 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

2.3. Visualization Dataand informationneed tobevisualized forbetter user experiences andservices.For example, thelargevolumeofnumericaldata(usually intabularform)canbetransformed intodifferent formats.Consequently, userunderstandability canbe increased.Thecapa- bilityof supporting timelydecisionsbasedonvisualizingbigdata is essential tovarious domains, namely tourism.Moreover, to identify relevant information to assist decision- making, apanel containing, inavisual and friendlyway, the reported insightsand infor- mation from the data analysis should be developed.All the information should be pre- sentedclearlyandefficientlyviastatisticalgraphics,plotsandinformationgraphics.This is essential for a decisionmaker to understand notmerely the events that occur in the specific location, butmore importantly,where theyoccur, that is, the spatial distribution ofevents. 3. RiseWiseApproach Our primary goal for our work is to evaluate our data-driven approach as an efficient computational instrument togenerateandvisualizeknowledgefromtourism-relateddata analysis.Toachieve this aim, the followingspecificsobjectiveshavebeendefined: • Identificationofrelevantprimary(official)andsecondary(e.g.,onlinesocialdata) tourismdata sources; • Todiscover structure inside unstructured data, extractmeaning fromnoisy data, findpatterns inapparentlyrandomdata,anduseall this informationtounderstand better trends,patterns, correlationsbyusingdatamining techniques; • To study, design, and implement algorithms that can extract tourism-related in- formationautomatically (i.e.,withouton-linehumanguidance)byusingmachine learning techniques togiving the capability to learn (statistical learning)without beingexplicitlyprogrammed; • Extraction of valuable information from the achievement of previous goals to study, encode and create knowledge regarding the phenomena that will be ad- dressedusingstate-of-artArtificial Intelligencemethods; Therefore,weareworking in a technological environment thatwill enhance: 1) the understandingoflarge-scaledata(relatedtoaccessibleandinclusivetourism)aggregated acrossmultiple and heterogeneous sources to garnering some deep insights; 2) the dy- namic application of analytics (exploratory, descriptive and diagnostic) and prediction algorithms tounveilpatternsdriving inclusiveandaccessible tourism;3) thedatavisual- ization through a dashboards/interfaces (presenting high-level summary of data and in- formation and having reporting capabilities); 4) themeans to allow the open access to the project’s data and scientific outcomes to the scientific community.Wewill address someof theaforementionedchallengesasdescribed in the followings. 3.1. OpenDataandExpertData Exploring or analyzing data leads to new insights, hypotheses, and questions that fuel further investigation before data can be examined or analyzed needs to be collected. Meanwhile, some concerns should be taken into account.Namely, themanipulation of M.GomesandP.Novais /AData-DrivenTool toPromoteTourism forPeoplewithDisabilities 49