@proceedings {433,
	title = {A Hospital Cloud-Based Archival Information System for the Efficient Management of HL7 Big Data},
	journal = {2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)},
	year = {2016},
	pages = {406 - 411},
	publisher = {IEEE Computer Society},
	address = {30 Ma - 3 June 2016 - Opatija, Croazia},
	abstract = {<p class="rtejustify">Nowadays, the Open Archive Information System (OAIS) model is widely adopted in hospitals to manage data related to both doctors and patients. However, the Archival Storage systems of hospitals are typically based on old Relational DBMS that makes hard the management of patients{\textquoteright} data especially in HL7 format. In fact, data have to be continuously parsed in order to be stored in relational \&nbsp;databases and sent to other hospital systems. Considering also interoperable scenarios where HL7 data continuously grow, the management of patients{\textquoteright} information can become very hard. In this paper, we discuss an OAIS system able to manage HL7 Big Data. In particular, considering a case of study of HL7 glucose observations in JSON format, we demonstrate that in a \&nbsp;scalable scenario an archival storage for big data processing is more convenient for hospitals than traditional archival storage systems.</p>
},
	keywords = {Big Data, cloud computing, HL7, Hospital Information System., OAIS},
	issn = {978-953-233-088-5},
	doi = {10.1109/MIPRO.2016.7522177},
	url = {http://www.mipro.hr/MIPRO2016.DCVIS/ELink.aspx},
	author = {Antonio Celesti and Maria Fazio and Agata Romano and Massimo Villari}
}
