The document discusses the profile and skills required for information professionals in managing big data, emphasizing the emergence of new competencies and the evolving nature of their roles. It highlights key tasks such as data analysis, management, and preservation while acknowledging the importance of ethical considerations and legislation surrounding data use. The document concludes that there is a need for updated academic and professional training to equip these professionals for the complexities of big data management.

1. BIG DATA: PROFILE AND SKILLS OF THE
INFORMATION PROFESSIONAL
Luísa Alvim
University of Évora, CIDEHUS (Portugal)
QQML 2018
22 - 25 MAY 2018 | CHANIA, CRETE, GREECE

2. Summary
• Introduction
• Definition of Big data;
• Profile and skills of the information professional for Big Data management;
EDISON Project;
• Results and discussion;
• Conclusions and future work.
2

3. Introduction
3
• Big Data
• Profile and skills for
Big Data
management
• Information
Professional

4. Big data
4

5. Big Data
5
Source: http://bahia.ugr.es/bigdade/index.php/bigdata-snapshots/
3vs
• Volume
• Velocity
• Variety
Doug Laney (2001)

6. Big Data
6
Source. https://www.m-brain.com/home/technology/big-data-with-8-vs/

7. Big data
The different phases of the process
Source: https://www.slideshare.net/cloudITbetter/big-data-building-blocks-with-aws-cloud/
7
DECISION

8. Big Data Management Cycle
8
Source: http://www.sanborn.com/the-big-geospatial-data-management-lifecycle/

9. Big Data Management
Data scientist
European e-Competence Framework
9
The Skills Framework for the Information Age - SFIA

10. Source: http://edison-project.eu/
10

11. Big Data management / EDISON
1. Data analysis;
2. Software and hardware development;
3. Skills and knowledge of scientific subjects (in the scope of business);
4. Data management and preservation;
5. Research methods.
11

12. Results and discussion
EDISON Project – data scientist
Information Professional:
• it works for the quality of life of the data and of the knowledge;
• it analyzes the data and facilitates organizations to generate knowledge for
action through the creation of information products;
• knowledge about legislation that affects data protection;
• the ethical aspects of information use;
• the knowledge about data preservation and recovery in user-oriented systems;
• ease of access and usability.
12

13. Results and discussion
Research data
13
Source: https://www.rd-alliance.org/
Source: http://forumgdi.rcaap.pt/
Source: http://www.dcc.ac.uk/events/research-data-management-forum-rdmf

14. 14
Source: http://www.datainfolit.org/
Results and discussion
Data Literacy

15. Conclusions
• Big Data creates new opportunities for the development of new skills of the information
professional;
• The profile of the manager can be considered to be under construction - EDISON;
• Open data;
• The information professional is an expert who may be of utmost importance for the
management of Big Data;
• The new profile and the new ways of acting of the professional of the information require a
renewed academic and professional formation, oriented to the problematics of the scientific
field in which the multiple tasks of the manager of Big Data are inserted.
15

16. References
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Documentación, (36). Retrieved from http://bid.ub.edu/es/36/alonso.htm&gt
CEN European Committee for Standardization. (2014). European e-Competence Framework 3.0. Retrieved from http://www.ecompetences.eu/wp-
content/uploads/2014/02/European-e-Competence-Framework-3.0_CEN_CWA_16234-1_2014.pdf
Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171–209. http://doi.org/10.1007/s11036-013-0489-0
Conselho Europeu das Associações de Informação e Documentação. (2005). Euro-Referencial I-D. Lisboa: INCITE.
Costa, C., & Santos, M. (2017). The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information
age. International Journal of Information Management.
Demchenko, I., & Belloum, A. (2016). Data Science competence framework: Approch and first working. EDISON Discussion Document. Retrieved from http://edison-
project.eu/sites/edison-project.eu/files/attached_files/node-29/edison-cf-ds-draft-cc-v06.pdf
Demchenko, I., & Belloum, A. (2017). EDISON: Discussion Document: Part 1. Data Science Competence Framework (CF-DS) release 2. Retrieved from http://edison-
project.eu/sites/edison-project.eu/files/filefield_paths/edison_cf-ds-release2-v08_0.pdf
EDISON Project UE. (2015). EDISON: Building the data science profession. Retrieved from http://edison-project.eu/
García Alsina, M. (2017). Big Data: Gestión y explotación de grandes volúmenes de datos. Barcelona: Editorial UOC.
O’Reilly Media. (2017). Big Data Now. United States of America: O’Reilly Media.
Ochôa, P. (2017). Painel Perfis e competências profissionais. In Encontro Curadoria Digital – Estratégias e experiências: atas.
Príncipe, P., & Furtado, F. (2017). Relatório do 2o Fórum de Gestão de Dados de Informação. Retrieved from http://hdl.handle.net/1822/46338
Research Data Alliance. (2016). 23 coisas: Bibliotecas e Dados Científicos.
SAS. (2013). Big Data Analytics: An assessment of demand for labour and skills, 2012-2017. London. Retrieved from
file:///C:/Users/luisa/Downloads/BigDataAnalyticsAnassessmentofdemandforlabourandskills2012-2017 (1).pdf
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17. Luísa Alvim
mluisa.alvim@gmail.com
Thank you
Research work carried out within the scope of UID/HIS/00057/2013 (POCI-01-
0145-FEDER-007702), FCT/Portugal, COMPETE, FEDER, Portugal2020.