Data Science & Engineering Consortium Initiative

Transcription

1 Data Science & Engineering Consortium Initiative A vision from the University of Santiago de Compostela Alberto Bugarín Affiliated Researcher Centro Singular de Investigación en Tecnoloxías da Información UNIVERSIDADE DE SANTIAGO DE COMPOSTELA citius.usc.es Real Academia de Ingeniería 12 marzo 2015

2 DSci&Eng. Vision from the USC Why a network in Data Science and Engineering (part ii) 1. Why a network in Data Science and Engineering (part ii)? 2. A vision from the USC 2

3 DSci&Eng. Vision from the USC Why a network in Data Science and Engineering (part ii) A new paradigm Big Data that has enabled Data Science Storing: the infrastructure Data engineering Cloud, Grid Computing Analytics: data information knowledge wisdom. Algorithmics Data mining, Knowledge Data Discovery Visualization: an image is worth a thousand words Graphical interfaces 3

4 Why a network in Data Science and Engineering (part ii) 4

5 DSci&Eng. Vision from the USC Why a network in Data Science and Engineering (part ii) Data Science Venn Diagram (Drew Conway, 2010): science is about discovery and building knowledge 5

6 Why a network in Data Science and Engineering (part ii) Can we train someone to become a data scientist or are they born to be a data scientist? 6

7 Why a network in Data Science and Engineering (part ii) Data visualization 7

8 Why a network in Data Science and Engineering (part ii) According to IBM, more than 2,5E30 bytes are generated per day. 90% of data in the world were generated in the last two years Enrique Dans (enriquedans.com) Progress and innovation are no longer hampered by the ability to gather data, but by the ability to Manage Analyze Synthesize Visualize, and discover knowledge from data collected in a timely manner and in a scalable way We are rich in data but poor in knowledge Francisco Herrera, University of Granada 8

9 Why a network in Data Science and Engineering (part ii) From all of the above, the need for building a network in the Data Science and Engineering is straightforward Complementary approaches Different expertise backgrounds Fields of application: from data to Products Services Applications (being aware that Technologies Previous positive experience in other networks Scientific and technological cooperation Entrepeneurship 9

10 A vision from the USC University of Santiago de Compostela Undergraduate programs in five fields of knowledge: Arts and Humanities (9) Sciences (4) Health (8) Social Sciences (14) Engineering (9) 65 post-graduate programs 54 doctoral programs 10

11 A vision from the USC Data science related programs: Undergraduate: Computer Science Mathematics Masters High performance computing Technologies for analysis of Big data Industrial mathematics Statistical techniques Doctoral Programs Research on Information Technologies Mathematical methods and numerical simulation Statistical and operations research 11

12 A vision from the USC Research Centre on Information Technologies (CiTIUS) UNIDAD DE PROYECCIÓN INTERNACIONAL RIAIDT EMPRENDIA CeBEGa UNIDAD DE PROMOCIÓN Y VALORIZACIÓN 12

13 CiTIUS A vision from the USC External Scientific Comission i. Inteligent Systems ii. Computer Architecture iii. Computer Vision Research Lines i. Medical Informatics ii. Robotics and Vision iii. Digital Contents Application Fields Scientific Units U1. Intelligent Systems U2. Computer Engineering U3. Visual Information U4. Systems Engineering Scientific Programs P1. E-Health P2. Ambient Intelligence and Multimodal Interfaces P3. Intelligent Web P4. Personal Robotics P5. Artificial Vision P6. High Performance Computing and Cloud Computing P7. Business Intelligence P8. Data Engineering 13

14 CiTIUS A vision from the USC 9 support technician s 82 JCR Papers M in R+D projects novel researchers 32 affiliated researchers USA patents + 1 OEPM patents + 1 Spin-off: Cilenis, Ubiplay Mobile y SITUM

15 CiTIUS A vision from the USC CWTS Leiden Ranking 2013, Mathematics and Computer Science Indicador Europe Number of cites normalized mean 1st (2.05) Number of cites mean 2 nd (3.53) Mean number of papers among 10% most cited 4th (15.4%) Ranking ISI 2012 of Spanish Universities Information and Communication Technologies IFQ2A Global 6th (0.226) Qualitative 2 nd (0.737) Cuantitative 13th (0.306) 15

16 A vision from the USC Scientific Programs 16

17 A vision from the USC An example: new services for daily life (real impact) Improving meteorological information to non-specialized users Intelligent reporting: explaining data using plain text (D2T systems) Natural Language Generation (NLG) techniques for automatic generation of individualized weather forecasts 17

18 A vision from the USC It is not always true that A picture is worth a thousand words There are studies that show how users prefer textual descriptions rather than figures or graphics or texts that help them to understand and interpret data So, many challenges remain to be addressed 18