Enabling instant- and interval-based semantics in multidimensional data models: the T+MultiDim Model

Combi, Carlo; Oliboni, Barbara; Pozzi, Giuseppe; Sabaini, Alberto; Zimányi, Esteban

doi:10.1016/j.ins.2019.12.074

Cited by 9 publications

(2 citation statements)

References 22 publications

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“…Seperti terlihat pada Tabel 3, terdapat 5 artikel MRDW pada kelompok perancangan yang terbit dari rentang tahun 2019-2021 dengan berbagai jenis fasilitas kesehatan sebagai subjek penerapan rancangan data warehouse [20,21,22,12,23]. Semua artikel tersebut mempunyai garis besar tujuan yang sama, yaitu untuk memudahkan akses data pasien antar fasilitas kesehatan yang berbeda, dokter yang berbeda, maupun pasien itu sendiri untuk memonitor kesehatan.…”

Section: Medical Record Data Warehouse (Mrdw)unclassified

Healthcare warehouse: Integrated literature review

Normasari,

Pandan Sari,

Widiyaningsih

et al. 2023

Angkasa

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Gudang atau warehouse berperan penting dalam sistem logistik suatu industri atau perusahaan. Namun demikian, pengetahuan tentang healthcare warehouse yang telah dikembangkan dalam beberapa tahun terakhir masih kurang. Untuk itu, maka artikel ini menyajikan integrated literature review pertama tentang healthcare warehouse melalui pencarian di penyimpanan dari basis data Scopus. Dengan menelusuri setiap artikel terkait dengan topik tersebut, didapatkan 24 artikel yang diterbitkan dari tahun 2013-2022 dan diklasifikasikan menjadi dua topik utama: goods warehouse sebanyak 4 artikel, dengan fokus healthcare yang terdapat pada fasilitas kesehatan, dan data warehouse sebanyak 20 artikel, yang memiliki fokus pada healthcare berisi berbagai jenis data, contohnya rekam medis, barang, dan data penyakit tertentu. Semua pengetahuan yang ada dalam studi ini dirangkum sehingga pembaca (baik akademisi maupun praktisi) dapat dengan mudah mengakses kontribusi utama dan informasi yang ada dalam setiap studi.

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Section: Medical Record Data Warehouse (Mrdw)unclassified

Healthcare warehouse: Integrated literature review

Normasari,

Pandan Sari,

Widiyaningsih

et al. 2023

Angkasa

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“…The source datasets include information about COVID-19, health and treatment status, places of hospitalization or self-isolation, patients personal data, geotracking data, social communications, which are processed using OLAP technologies. OLAP information technology is based on a multidimensional data model that contains basic entities, in particular, the data hypercube rel, dimension D, attribute A, cell X, value rel (D,A) [25]. Multidimensional analysis of COVID-19 data provides research and analysis of the characteristics of municipal and open medical and sociocommunication resources, including the choice of a set of attributes used for parameterization of the information model [26][27][28][29][30] (Fig.…”

Section: Multidimensional Representation Of Covid-19mentioning

confidence: 99%

Multidimensional Representation of COVID-19 Data Using OLAP Information Technology

Duda

Pasichnyk

Kunanets

et al. 2020

2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT)

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In December 2019, an unknown disease was first reported in Wuhan (Hubei province, China), which subsequently spread around the world. COVID-19 is an infectious disease accompanied by severe acute respiratory syndrome (SARS-CoV-2) [1], which is called a "coronavirus" for the visual similarity of the pathogen to the crown [2]. On April 23 2020, the World Health Organization has identified more than 2.5 million confirmed cases of COVID-19 virus disease[3]. Considering the scope of spread and features of the pandemic caused by the COVID-19 virus, timely diagnosis of the disease of citizens is important. The first step in developing any diagnostic or treatment tools is to effectively process data collections, much of which are based on open data from national, provincial, and municipal health facilities. At the same time, the importance of IT support the processes of making operational and strategic decisions in the health sector, as a critical area of smart cities and smart regions is increasing. Therefore, developing effective and reliable means of generating and processing detailed collections of COVID-19 outbreaks in real-time is an important research area in the implementation of innovative information technology projects of the smart city and smart region class. It requires design, development and implementation of information technology and software-algorithmic tools to collect and process data globally.

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