An Ontology based Hybrid Approach to Derive Multidimensional Schema for Data Warehouse

Thenmozhi, M.; Vivekanandan, K.

doi:10.5120/8590-2343

Cited by 25 publications

(25 citation statements)

References 21 publications

(31 reference statements)

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“…They adopted ontology reasoning to automatically generate multidimensional components, e.g. facts and dimensions [6]. Insight of our research is quite similar with the notion of the all mentioned research works above, which is to present entities relationship in the data warehouse with a better visual that can be easily understood and used by users.…”

Section: Introductionmentioning

confidence: 55%

Visualization of Ontology-Based Data Warehouse for Malaria Spread Incidences Using Protege

Kardiana

Diana

2016

Jurnal Sistem Informasi

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Malaria is a communicable disease caused by a plasmodium parasite and transmitted among human by Anopheles mosquitoes. Late medication of this disease can cause a death of patients. Indonesia has many endemic areas with a high volume of patients diagnosed by Malaria. Currently, this incidences data is stored in Microsoft Excel files. We need to build a data warehouse to easily manage these data. Here, we create ontology of Malaria's incidence data to figure out the important information in Malaria data warehouse that we want to build. We identify entities, classes, subclasses, and relationships between these entities. We employed Protégé to build and visualize the ontology of Malaria incidence data. Keywords: ontology, data warehouse, malaria, visualization, Protégé AbstrakMalaria adalah penyakit menular yang disebabkan oleh parasite plasmodium dan dipindahkan ke tubuh manusian oleh Nyamuk Anopheles. Penanganan yang lambat terhadap penyakit malaria dapat menyebabkan kematian pasien. Indonesia adalah salah satu negara yang memiliki banyak wilayah endemik dengan volume yang cukup tinggi terhadap pasien didiagnosis penyakit malaria. Saat ini, data dari kasus-kasus malaria di berbagai wilayah endemic di Indonesia masih disimpan dalam banyak file excel. Akibatnya, terdapat kesulitan untuk memperoleh informasi yang cepat dalam pengambilan keputusan untuk penanganan kasus malaria. Oleh karena itu, perlu dibangun sebuah data warehouse untuk mengatur data tersebut secara terpusat. Pada artikel ini, dibuat ontology untuk mengidentifikasi informasi dan parameter penting dari elemen-elemen yang harus ada dalam data warehouse, seperti: entitas, kelas, sub-kelas, dan hubungan antar entitas. Protégé digunakan untuk membangun visualisasi dan memudahkan pemahaman terhadap hubungan antar entitas dalam data kasus malaria.

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Section: Introductionmentioning

confidence: 55%

Visualization of Ontology-Based Data Warehouse for Malaria Spread Incidences Using Protege

Kardiana

Diana

2016

Jurnal Sistem Informasi

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“…Studies that focused on the stage of transformation and loading and the use of ontologies included: Skoutas and Simitsis (), Skoutas and Simitsis (), Nazri et al (), Salguero et al (), Sell et al (), Salguero et al (), Spahn et al (), Skoutas et al (), Niinimäki and Niemi (), Simitsis et al (), Jiang et al (), Romero et al (), Bergamaschi et al (), Martin et al (), Thenmozhi and Vivekanandan (), Ali et al (), Elamin and Feki (), Ramasamy and Palanivel (), Samuel (), Di et al (), Steiner et al (), Ravat et al (), and Nebot and Berlanga ().…”

Section: Resultsmentioning

confidence: 99%

“…Such studies were considered evaluations of the proposal. Studies that proposed specific solutions and evaluated their proposals included: Skoutas and Simitsis (), Spahn et al (), Niinimäki and Niemi (), Romero and Abelló (), Jiang et al (), Romero et al (), Selma et al (), Thenmozhi and Vivekanandan (), Etcheverry and Vaisman (), Samuel (), Lamolle et al (), Nebot and Berlanga (), and Ravat et al (). Studies that proposed specific solutions that were evaluated using an example included: Skoutas and Simitsis (), Niemi et al (), Nazri et al (), Salguero et al (), Sell et al (), Salguero et al (), Bergamaschi et al (), Martin et al (), Sell et al (), Thenmozhi and Vivekanandan (), Ali et al (), Khouri et al (), Elamin and Feki (), Talebzadeh et al (), El Sarraj et al (), Di et al (), and Steiner et al ().…”

Section: Resultsmentioning

confidence: 99%

“…Figure 7 shows that the majority of primary studies are concentrated in the stage of transformation and loading, and in the use of ontologies, rather than in the use of some language such as RDF or OWL. Studies that focused on the stage of transformation and loading and the use of ontologies included: Skoutas and Simitsis (2006), Skoutas and Simitsis (2007), Nazri et al (2008), Salguero et al (2008a), Sell et al (2008), Salguero et al (2008b), Spahn et al (2008), Skoutas et al (2009), Niinimäki and Niemi (2009), Simitsis et al (2010), Jiang et al (2010), Romero et al (2011), Bergamaschi et al (2011), Martin et al (2011), Thenmozhi and Vivekanandan (2012), Ali et al (2013), Elamin and Feki (2014), Ramasamy and Palanivel (2014), Samuel (2014), Di et al (2015), Steiner et al (2015), Ravat et al (2016), and Nebot and Berlanga (2016).…”

Section: Rq2-what Semantic Web Technologies Are Being Used In Dw Devementioning

confidence: 99%

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Using Semantic Web technologies in the development of data warehouses: A systematic mapping

Gacitúa

Mazón

Cravero

2018

WIREs Data Min & Knowl

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The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers. This article is categorized under: Fundamental Concepts of Data and Knowledge > Information Repositories Fundamental Concepts of Data and Knowledge > Knowledge Representation Algorithmic Development > Web Mining

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“…Requirement analysis, which is based on the i* framework to represent user requirements; 2. Source integration, which produces an integrated schema by reconciling data sources using an ontological approach [27,28,29,30]. 3.…”

Section: Modelsmentioning

confidence: 99%

A Proposal of Methodology for Designing Big Data Warehouses

Tria¹,

Lefons²,

Tangorra³

2018

Preprint

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Big Data warehouses are a new class of databases that largely use unstructured and volatile data for analytical purpose. Examples of this kind of data sources are those coming from the Web, such as social networks and blogs, or from sensor networks, where huge amounts of data may be available only for short intervals of time. In order to manage massive data sources, a strategy must be adopted to define multidimensional schemas in presence of fast-changing situations or even undefined business requirements. In the paper, we propose a design methodology that adopts agile and automatic approaches, in order to reduce the time necessary to integrate new data sources and to include new business requirements on the fly. The data are immediately available for analyses, since the underlying architecture is based on a virtual data warehouse that does not require the importing phase. Examples of application of the methodology are presented along the paper in order to show the validity of this approach compared to a traditional one.

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An Ontology based Hybrid Approach to Derive Multidimensional Schema for Data Warehouse

Cited by 25 publications

References 21 publications

Visualization of Ontology-Based Data Warehouse for Malaria Spread Incidences Using Protege

Visualization of Ontology-Based Data Warehouse for Malaria Spread Incidences Using Protege

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

A Proposal of Methodology for Designing Big Data Warehouses

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