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dc.contributor.authorMalik, K.R.
dc.contributor.authorFarhan, M.
dc.contributor.authorHabib, M.A.
dc.contributor.authorKhalid, S.
dc.contributor.authorAhmad, M.
dc.contributor.authorGhafir, Ibrahim
dc.date.accessioned2020-01-24T12:23:36Z
dc.date.accessioned2020-02-10T14:51:17Z
dc.date.available2020-01-24T12:23:36Z
dc.date.available2020-02-10T14:51:17Z
dc.date.issued2018-04
dc.identifier.citationMalik KR, Farhan M, Habib MA et al (2018) Remote access capability embedded in linked data using bi-directional transformation: issues and simulation. Sustainable cities and Society. 38: 662-674.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17620
dc.descriptionNoen_US
dc.description.abstractMany datasets are available in the form of conventional databases, or simplified comma separated values. The machines do not adequately handle these types of unstructured data. There are compatibility issues as well, which are not addressed well to manage the transformation. The literature describes several rigid techniques that do the transformation from unstructured or conventional data sources to Resource Description Framework (RDF) with data loss and limited customization. These techniques do not present any remote way that helps to avoid compatibility issues among these data forms simultaneous utilization. In this article, a new approach has been introduced that allows data mapping. This mapping can be used to understand their differences at the level of data representations. The mapping is done using Extensible Markup Language (XML) based data structures as intermediate data presenter. This approach also allows bi-directional data transformation from conventional data format and RDF without data loss and with improved remote availability of data. This is a solution to the issue concerning update when dealing with any change in the remote environment for the data. Thus, traditional systems can easily be transformed into Semantic Web-based system. The same is true when transforming data back to conventional data format, i.e. Database (DB). This bidirectional transformation results in no data loss, which creates compatibility between both traditional and semantic form of data. It will allow applying inference and reasoning on conventional systems. The census un-employment dataset is used which is being collected from US different states. Remote bi-directional transformation is mapped on the dataset and developed linkage using relationships between data elements. This approach will help to handle both types of data formats to co-exist at the same time, which will create opportunities for data compatibility, statistical powers and inference on linked data found in remote areas.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1016/j.scs.2018.01.047en_US
dc.subjectBi-directional data transformationen_US
dc.subjectCensus dataen_US
dc.subjectLinked dataen_US
dc.subjectRemote accessen_US
dc.subjectEnrichment of census dataen_US
dc.subjectApplication of semantic weben_US
dc.titleRemote access capability embedded in linked data using bi-directional transformation: issues and simulationen_US
dc.status.refereedYesen_US
dc.date.Accepted2018-01-28
dc.date.application2018-02-02
dc.typeArticleen_US
dc.type.versionNo full-text in the repositoryen_US
dc.date.updated2020-01-24T12:23:38Z
refterms.dateFOA2020-02-10T14:51:49Z


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