- -

Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case

Mostrar el registro completo del ítem

Galvão, J.; León-Palacio, A.; Costa, C.; Santos, MY.; Pastor López, O. (2020). Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case. Springer Nature. 3-19. https://doi.org/10.1007/978-3-030-63396-7_1

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/179859

Ficheros en el ítem

Thumbnail
Nombre: GalvaoLeon-Palaci ...
Tamaño: 895.3Kb
Formato: PDF
Descripción: Versión del Autor.
Abrir/Preview
[Cerrado]
Nombre: EMCIS2020 - Towards ...
Tamaño: 2.151Mb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor

Metadatos del ítem

Título: Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case
Autor: Galvão, João León-Palacio, Ana Costa, Carlos Santos, Maribel Yasmina Pastor López, Oscar
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] Data Warehousing applied in Big Data contexts has been an emergent topic of research, as traditional Data Warehousing technologies are unable to deal with Big Data characteristics and challenges. The methods used in ...[+]
Palabras clave: Data Warehousing , Big data modelling , Conceptual modeling
Derechos de uso: Reserva de todos los derechos
ISBN: 978-3-030-63395-0
Fuente:
Information Systems. 17th European, Mediterranean, and Middle Eastern Conference, EMCIS 2020, Dubai, United Arab Emirates, November 25-26, 2020, Proceedings. (issn: 1865-1348 )
DOI: 10.1007/978-3-030-63396-7_1
Editorial:
Springer Nature
Versión del editor: https://doi.org/10.1007/978-3-030-63396-7_1
Título del congreso: 17th European, Mediterranean and Middle Eastern Conference on Information Systems (EMCIS 2020)
Lugar del congreso: Online
Fecha congreso: Noviembre 25-26,2020
Serie: Lecture Notes in Business Information Processing;402
Código del Proyecto:
info:eu-repo/grantAgreement/FCT//UID%2FCEC%2F00319%2F2019/
...[+]
info:eu-repo/grantAgreement/FCT//UID%2FCEC%2F00319%2F2019/
info:eu-repo/grantAgreement/FCT//PD%2FBDE%2F135100%2F2017/
info:eu-repo/grantAgreement/FEDER//POCI-01-0247-FEDER-039479/
info:eu-repo/grantAgreement///TIN2016-80811-P//UN METODO DE PRODUCCION DE SOFTWARE DIRIGIDO POR MODELOS PARA EL DESARROLLO DE APLICACIONES BIG DATA/
info:eu-repo/grantAgreement///PROMETEO%2F2018%2F176//GISPRO-GENOMIC INFORMATION SYSTEMS PRODUCTION/
info:eu-repo/grantAgreement///ACIF%2F2018%2F171//SOPORTE ONTOLOGICO Y TECNOLOGICO PARA EL DESARROLLO DE APLICACIONES BIG DATA./
[-]
Agradecimientos:
This work has been supported by FCT - Fundação para a Ciên-cia e Tecnologia within the Project Scope: UID/CEC/00319/2019, the Doctoral scholarship PD/BDE/135100/2017 and European Structural and Investment Funds in the FEDER ...[+]
Tipo: Comunicación en congreso Artículo Capítulo de libro

References

Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann is an imprint of Elsevier, Amsterdam (2013)

Santos, M.Y., Costa, C.: Big Data: Concepts, Warehousing and Analytics. River Publishers, Aalborg (2020)

Cuzzocrea, A., Moussa, R.: Multidimensional database modeling: literature survey and research agenda in the big data era. In: 2017 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1–6 (2017) [+]
Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann is an imprint of Elsevier, Amsterdam (2013)

Santos, M.Y., Costa, C.: Big Data: Concepts, Warehousing and Analytics. River Publishers, Aalborg (2020)

Cuzzocrea, A., Moussa, R.: Multidimensional database modeling: literature survey and research agenda in the big data era. In: 2017 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1–6 (2017)

Di Tria, F., Lefons, E., Tangorra, F.: Design process for big data warehouses. In: 2014 International Conference on Data Science and Advanced Analytics (DSAA), pp. 512–518. IEEE (2014)

Dehdouh, K., Bentayeb, F., Boussaid, O., Kabachi, N.: Using the column oriented NoSQL model for implementing big data warehouses. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) (2015)

Bézivin, J.: On the unification power of models. Softw. Syst. Model. 4(2), 171–188 (2005). https://doi.org/10.1007/s10270-005-0079-0

Reyes Román, J.F., Pastor, Ó., Casamayor, J.C., Valverde, F.: Applying conceptual modeling to better understand the human genome. In: Comyn-Wattiau, I., Tanaka, K., Song, I.-Y., Yamamoto, S., Saeki, M. (eds.) ER 2016. LNCS, vol. 9974, pp. 404–412. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46397-1_31

Embley, D.W., Liddle, S.W.: Big data—conceptual modeling to the rescue. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 1–8. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41924-9_1

Giebler, C., Gröger, C., Hoos, E., Schwarz, H., Mitschang, B.: Modeling data lakes with data vault: practical experiences, assessment, and lessons learned. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 63–77. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33223-5_7

Gil, D., Song, I.-Y.: Modeling and management of big data: challenges and opportunities. Future Gener. Comput. Syst. 63, 96–99 (2016)

Di Tria, F., Lefons, E., Tangorra, F.: GrHyMM: a graph-oriented hybrid multidimensional model. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER 2011. LNCS, vol. 6999, pp. 86–97. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24574-9_12

Santos, M.Y., Costa, C.: Data warehousing in big data: from multidimensional to tabular data models. In: Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, pp. 51–60. ACM, New York (2016)

Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley, Hoboken (2013)

Costa, C., Santos, M.Y.: Evaluating several design patterns and trends in big data warehousing systems. In: Krogstie, J., Reijers, H.A. (eds.) CAiSE 2018. LNCS, vol. 10816, pp. 459–473. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91563-0_28

Santos, M.Y., Costa, C., Galvão, J., Andrade, C., Pastor, O., Marcén, A.C.: Big data warehousing for efficient, integrated and advanced analytics - visionary paper. In: Cappiello, C., Ruiz, M. (eds.) CAiSE 2019. LNBIP, vol. 350, pp. 215–226. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21297-1_19

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem