Computing and data science.

Data analysis, advanced visualization and software development

Head of the Research Line:

Gonzalo Ruiz

Researchers:

Alfredo Ferrer
David Iñiguez
Álvaro Martín
David Muñoz
Francho Bauzá

SUMMARY

The main goal of this team is to research and support research whenever software development or data analytics are involved in the process. To achieve this, one of the most important tasks carried out is the participation in projects in which we collaborate with companies or other research groups. These collaborations are focused on topics such as BigData, Machine Learning, Internet analysis, social networks, distributed computing, new technologies in education, etc. The levels of collaboration range from small contributions to local companies or research groups to international projects.

The other task that we carry out in the BIFI is to support those researches that are being carried out; improving and optimizing programs that already exist, and conducting consulting work on the best technologies and techniques for development.

Relevant publications

1. Targeted Community Merging provides an efficient comparison between collaboration clusters and departmental partitions. F J Bauza, G Ruiz-Manzanares, J Gómez-Gardeñes, A Tarancón, D Íñiguez, Targeted Community Merging provides an efficient comparison between collaboration clusters and departmental partitions, Journal of Complex Networks, Volume 11, Issue 2, April 2023, cnad012, https://doi.org/10.1093/comnet/cnad012
2. Analysis of the evolution and collaboration networks of citizen science scientific publications. Pelacho, M., Ruiz, G., Sanz, F. et al. Analysis of the evolution and collaboration networks of citizen science scientific publications. Scientometrics 126, 225–257 (2021). https://doi.org/10.1007/s11192-020-03724-x
3. Leaders among the leaders in Economics: a network analysis of the Nobel Prize laureates. José Alberto Molina, David Iñiguez, Gonzalo Ruiz & Alfonso Tarancón (2021) Leaders among the leaders in Economics: a network analysis of the Nobel Prize laureates, Applied Economics Letters, 28:7, 584-589, DOI: 10.1080/13504851.2020.1764478
4. Use of open data to improve automobile insurance premium rating. Blesa, D. Iñiguez, R. Moreno, G. Ruiz.  International Journal of Market Research 1 – 21 (2019). DOI: 10.1177/1470785319862734.
5. Analyzing the potential impact of BREXIT on the European research collaboration network” F. Bauzá, G. Ruiz-Manzanares, L. Pérez-Sienes, A. Tarancón, D. Íñiguez and J. Gómez-Gardeñes. “. Chaos: An Interdisciplinary Journal of Nonlinear Science 30, 063145 (2020); DOI: 10.1063/1.5139019.
6. Identification of risk features for complication in Gaucher”s disease patients: A machine learning analysis of the Spanish registry of Gaucher disease. M.M. Andrade-Campos et al.  Orphanet Journal of Rare Diseases. 15 – 1, pp. 256 [11 pp]. 2020. ISSN 1750-1172. DOI: 10.1186/s13023-020-01520-7.
7. Analysis of academic productivity based on Complex Networks. September 2015, R. Álvarez, E. Cahué, J. Clemente-Gallardo, A. Ferrer, D. Íñiguez, X. Mellado, A. Rivero, G. Ruiz, F. Sanz, E. Serrano, A. Tarancón, Y. Vergara. Scientometrics, September 2015, Volume 104, Issue 3, pp 651-672.
8. RRLab: Remote Reality Laboratory to teach mechanics in schools. November 2013, Elisa Cauhé, Alfredo Ferrer, Gonzalo Ruiz, David Íñiguez, Alfonso Tarancón. Chapter 6 of the book “IT Innovative Practices in Secondary Schools: Remote Experiments”, Published by Deusto in 2013. ISBN: 978-84-15772-01-9
9. Hadoop Cloud SaaS access via WS-PGRADE adaptation. November 2012, Elisa Cauhé, Arturo Giner, Jaime Ibar, Gonzalo Ruiz, Ruben Vallés. 6th IBERIAN GRID INFRASTRUCTURE CONFERENCE PROCEEDINGS Pages: 161-172 Published: 2013
10. Heterogeneous networks do not promote cooperation when humans play a Prisoner‘s Dilemma. 8th June 2012, Carlos Gracia-Lázaro, Alfredo Ferrer, Gonzalo Ruiz, Alfonso Tarancón, José A. Cuesta, Angel Sánchez, and Yamir Moreno. PNAS, Vol. 109, no. 32.
11. OptiWeb: An optimization application for steel cut industries ported to the Grid in the framework of PireGrid project. 5th May 2011, “Proceedings of the 5th IBERGRID. ISBN: 978-84-9745-884-9”
12. Structural and Dynamical Patterns on Online Social Networks: The Spanish May 15th Movement as a Case Study. 30th July 2011, Javier Borge-Holthoefer, Alejandro Rivero, Íñigo García, Elisa Cauhé, Alfredo Ferrer, Darío Ferrer, David Francos, David Íñiguez, María Pilar Pérez, Gonzalo Ruiz, Francisco Sanz, Fermín Serrano, Cristina Viñas, Alfonso Tarancón, Yamir Moreno . PLoS ONE 6(8): e23883, 2011.

Main research projects

1. Participation in the “IOT-DITWICS Experiment” from EUHubs4Data federation. This European federation of Data Driven Innovation Hubs aims to establish itself as the European reference in data-driven innovation and experimentation, promoting collaboration between related initiatives in Europe, federating solutions in a common global catalog of data services and sharing data cross-border and cross-sector.
2. Partner of “EOSC-Synergy” H2020 project, whose goal is to expand the capacity and capabilities of the EOSC by leveraging the experience, effort and resources of publicly funded national digital infrastructures.
3. “DEEP CODE: Deep Learning System for characterization of clients, prediction and decision making in the insurance sector”, Collaboration Challenges project with the company Codeoscopic S.A, with funding from the Ministry of Economy and Competitiveness.
4. “OPTIWASTE – Machine learning models for forecasting and optimizing resources in waste management”, Collaboration Challenges project with the company Distromel S.A, with funding from the State Research Agency.
5. We participate in the “Aragón Open Data” Project, developing the social part, which consists of collecting information from the Internet (social networks, press, etc.) related to Aragon and presenting it in a structured format through an API to provide users with citizens tools to make their own applications.
6. Development of the application called Kampal, which creates and studies the networks formed by the members of the University of Zaragoza through their research and projects. The emphasis is on the relationships between people and the dynamics of interaction rather than individual properties.
   
7. Development of a platform that includes different didactic units focused on studying the Solar System through gestures thanks to the Microsoft Kinect device. These units were developed in collaboration with the Juan de Lanuza school in the context of its innovation class.
8. Participation in SEPS, INNPACTO Project that tries to predict different types of risks in electrical networks, and study their impact if they occur. In this Project we collaborate with companies and research groups such as Gas Natural Fenosa, Telvent (currently Schneider Electric), the Carlos III University or the University of Lleida.
9. RRLab (Remote Reality Laboratory): this Project, designed for educational purposes, consists of the creation of a web platform for conducting physics experiments remotely with the aim of allowing students to compare the theoretical results with reality.
   
10. Prisoner’s Dilemma Experiment: we developed a web platform to carry out collective experiments to study the behavior of people depending on the structure of their organization. This platform has been used to carry out two different experiments at the moment, and in one of them more than 1,300 students participated in real time. During the last years we have made different changes and improvements to the platform to study different parameters and variables and how they affect people’s behavior.
    
11. Feelicity: it was a project developed with TEDxZaragoza for the geotagging of users’ happy moments.
    
12. Collaboration in the Ibercivis Project carrying out different development tasks (visualization, web, customization of the BOINC client, etc.)
    
13. Participation in the STEREA Project “Optimization of Water Resources and Remote Irrigation Management” which consisted of one of the first web applications developed to manage the irrigation systems of different fields in order to optimize resources, reducing costs, and increasing productivity.
14. Participation in the SCIBUS project of the FPVII framework program, whose objective was to create a generic-purpose portal with a series of tools to provide simple and transparent access to computing, data, network and service infrastructures in Europe, including clusters, academic and commercial supercomputers, grids, desktop grids, and clouds.
15. Study of the 15M movement on Twitter: in this case, the group was in charge of different tasks related to the study such as visualization, data collection and processing, etc.
    
16. Optiweb: this project was developed in early 2011 in collaboration with the company Schnell Software, which consisted of optimizing one of its software products so that it used a GRID infrastructure in its execution, thus improving performance.

High Performance Computing (HPC)

Head of the Research Line:

David Íñiguez Dieste

Researchers:

Daniel Martínez Cucalón
John Díaz Laglera
Alfonso Tarancón Lafita

SUMMARY

The High Performance Computing and Cloud Computing (HPC-Cloud) group is structured around the following lines of work:

• The participation in national and international projects related to HPC and Cloud technologies, as well as in discussion forums and integration of these technologies both in research and in companies.
• The maintenance and support of BIFI’s supercomputing infrastructures, housed in the Aragón Supercomputing Center (CESAR). The group’s staff has extensive experience in management (operation, monitoring, accounting…) and support to users of large calculation systems for scientific use, as well as in the design and maintenance of data centers. The center houses two massively parallel supercomputers (CIERZO / CAESARAUGUSTA (III) and MEMENTO), the COLOSSUS cloud infrastructure, as well as other computing and data storage infrastructures.

• To offer a quality calculation and storage service for Institute researchers and other external users. The calculation systems we manage offer several million hours of calculation and hundreds of terabytes of storage annually, both to BIFI researchers and their collaborators, as well as to external users through the Spanish Supercomputing Network, the Hosted Clusters program and others. services provided.
• Other services: the porting, optimization and parallelization of applications. As an additional service to the basic support offered in the use of our supercomputers, we collaborate with our users to help them migrate and streamline their codes in the HPC environment.
• To serve as a test bed for Spanish and European companies and SMEs that seek the adoption of new technologies to improve their businesses, offering computational resources under the IaaS (Infrastructure as a Service) paradigm, as well as collaborating in the development and integration of applications business to the cloud.
• Training and dissemination. The group actively participates in these types of activities, teaching courses and tutorials, directing TFG / TFMs, tutoring company practices, managing guided visits to our facilities …
• To participate in the main supercomputing networks at national and European level: RES (Red Española de Supercomputación), Ibergrid (Spain and Portugal) and EGI-FedCloud, which is one of the largest distributed infrastructures worldwide.

Main research projects

1.- EuroCC. Creation of a European network of supercomputing centers at the service not only of research but also of companies. The project aims to promote national strengths in HPC competencies and fill existing gaps.

2.- EOSC-Synergy. Its objective is to expand the capabilities of EOSC (European Open Science Cloud) by taking advantage of the experience, effort and resources of national digital infrastructures funded with public funds.

3.- Cloudflow. European project in collaboration with the companies Nabladot and Biocurve. Improvement of the biomass boiler manufacturing process through adaptation of CFD (Computational Fluid Dynamics) software and deployment on the CloudFlow platform.

4.- FORTISSIMO. European project in collaboration with the company Schnell Software. Reinforcement cutting optimization in Cloud Computing environment.

5.- FORTISSIMO 2. European project focused on promoting the use of Cloud and Big Data technologies by companies, in collaboration with SMEs Nabladot and Kliux (in addition to the cloud provider Gompute).

5.- CloudSME (Simulation for manufacturing & engineering). European project in collaboration with the companies Inycom / Podoactiva. Migration of the 3D scanning system and template design to the CloudSME platform.

7.- SCC-Computing: establishment of a strategic collaboration with computer experts from China to develop the next calculation systems beyond Tianhe-1A (most powerful supercomputer in the world according to the top500 ranking in November 2010).

8.- EGI-Engage

9.- SCI-BUS (Scientific gateway Based User Support)

10.- AraGrid

11.- EGI-InSPIRE (European Grid Infrastructure)

12.- PireGrid

Special Purpose Computers

Head of the Research Line:

Sergio Pérez Gaviro

Researchers:

Andrés Cruz Flor
Luis Antonio Fernández Pérez (UCM)
Antonio Gordillo Guerrero (UNEX)
David Iñiguez Dieste
Víctor Martín Mayor(UCM)
Javier Moreno Gordo
Juan Jesús Ruiz Lorenzo (UNEX)
Alfonso Tarancón Lafita

SUMMARY

Computers have become an essential tool in our quotidian lives. Very simple daily mundane activities as train tickets booking or sending a message to someone require the use of conventional computers. Of course, they also play a very important role in more difficult tasks, such as bank transfers or power grid management for instance. On the other hand, computers have also made possible many advances in Science and nowadays are patently present in a very wide set of different scientific areas. Indeed, many institutions around the World spend a huge amount of money and human effort to build clusters of computers (see for example, www.top500.org/lists/ for a detailed ranked list of the most powerful supercomputers in the World).

However, for some specific problems, conventional computers are not enough. They would spend thousands of years to perform some particular calculations. So in the framework of supercomputing one finds the Special Purpose Computers, which are developed and designed to perform some specific computing-intensive calculation. The development of this kind of supercomputers is in fact the objective of this research line.

Thanks to a very successful scientific collaboration between researchers from BIFI and the Universidad de Zaragoza, Universidad Complutense de Madrid, Universidad de Extremadura, Università degli Studi di Roma “La Sapienza” and Università di Ferrara, the Janus supercomputer was born in 2008. It is a modular, massively parallel, and reconfigurable FPGA-based computing system for High Performance Scientific Computing. Its reconfigurable architecture permits Janus to afford different scientific computational applications, as in Physic, in Chemistry or in Biology. So far, the Janus Collaboration focused its efforts on the study and simulation of spin glasses, paradigm of complex systems.

Janus is composed by 16 boards. On each board, a bidimensional 4×4 grid of FPGA-processors is located and linked obeying periodic boundary conditions. Each of these processors is called SP (Simulation Processor) and carries on the simulations. A 17th FPGA is settled in the middle acting as a crossbar and called IOP (Inpu/Output Processor), in charge of all internal connections and external communications. All FPGA modules are Xilinx Virtex4-LX200.

Janus retired in 2020 after 12 years of non-stop activity. It is currently found as an exhibition article in the hall of the Faculty of Sciences of the University of Zaragoza.

The Janus II Special Purpose Computer is the new generation supercomputer located at BIFI from 2013. Following the same successful Janus philosophy, JanusII is composed again by 16 boards. On each board, 16 latest generation FPGA processors (Xilinx Virtex-7 XC7VX485T FPGA) are located and linked obeying periodic boundary conditions. They are called SP’s from “Simulation Processor”, since they will be in charge of the simulations. All SP’s on each board are controlled by a full fledged computer that we call CP (Control Processor), running the Linux operating system. These CP’s configure all FPGA processors for the simulations, controlling and monitoring their status. The CP uses a commercially available Computer-on-Module system (COM), based on an Intel Core i7 processor; it connects via the PCIe interface to a so-called Input-Output-Processor (IOP) built inside yet another FPGA. The IOP actually manages all connections to all SP’s, controlling the configuration procedure and their operation, and monitoring their status. The Janus II architecture includes also improved communications, permitting the interconnection between all boards, and it enlarges 100 times the memory available.

JanusII was built thanks to FEDER funds: Ministerio de Economía y Competitividad (Gobierno de España), Gobierno de Aragón, European Union.

More information: http://www.janus-computer.com

RELEVANT PUBLICATIONS

1.-Janus II: a new generation application-driven computer for spin-system simulations. Janus Collaboration: M. Baity-Jesi; R. A. Baños; A. Cruz; L. A. Fernandez; J. M. Gil-Narvion; A. Gordillo-Guerrero; D. Iñiguez; A. Maiorano; F. Mantovani; E. Marinari; V. Martin-Mayor; J. Monforte-Garcia; A. Muñoz Sudupe; D. Navarro; G. Parisi; S. Perez-Gaviro; M. Pivanti; F. Ricci-Tersenghi; J. J. Ruiz-Lorenzo; S. F. Schifano; B. Seoane; A. Tarancon; R. Tripiccione; D. Yllanes. Ref.: Computer Physics Communications 185; 550-559 (2014).. DOI: https://doi.org/10.1016/j.cpc.2013.10.019¡

2. An FPGA-Based Supercomputer for Statistical Physics: the Weird Case of Janus.  Janus Collaboration: R. A. Banos; A. Cruz; L. A. Fernandez; J. M. Gil-Narvion; A. Gordillo-Guerrero; M. Guidetti; D. Iniguez ; A. Maiorano; F. Mantovani; E. Marinari ; V. Martin-Mayor; J. Monforte-Garcia; S. Perez-Gaviro A. Muñoz Sudupe; D. Navarro; G. Parisi; M. Pivanti; S. Perez-Gaviro; F. Ricci-Tersenghi; J. J. Ruiz-Lorenzo; S. F. Schifano; B. Seoane; A. Tarancon; R. Tripiccione; D. Yllanes. Ref: Book Chapter in Book: “High-Performance Computing using FPGAs”; pp 481-506 (2013). University of Glasgow; Publisher: Springer-Verlag, New York. DOI: https://doi.org/10.1007/978-1-4614-1791-0_16

3. Spin glass simulations on the Janus architecture: A desperate quest for strong scaling. Janus Collaboration: M. Baity-Jesi; R.A. Baños; A. Cruz; L.A. Fernandez; J.M. Gil-Narvion; A. Gordillo-Guerrero; M. Guidetti; D. Iñiguez; A. Maiorano; F. Mantovani; E. Marinari; V. Martin-Mayor; J. Monforte-Garcia; A. Muñoz-Sudupe; D. Navarro; G. Parisi; S. Perez-Gaviro; M. Pivanti; F. Ricci-Tersenghi; J. Ruiz-Lorenzo; S.F. Schifano; B. Seoane; A. Tarancon; P. Tellez; R. Tripiccione ; D. Yllanes. Ref: Book Chapter in Conference proceedings book: “Euro-Par 2012: Parallel Processing Workshops”. Lecture Notes in Compouter Science; Volume 7640; 2013; Pages 528-537. Publisher: Springer-Verlag, Berlin Heidelberg. Part of the Lecture Notes in Computer Science book series (LNCS, volume 7640) DOI: https://doi.org/10.1007/978-3-642-36949-0_61

4. Reconfigurable computing for Monte Carlo simulations: results and prospects of the Janus project. Janus Collaboration: M. Baity-Jesi, R. A. Banos, A. Cruz, L. A. Fernandez, J. M. Gil-Narvion, A. Gordillo-Guerrero, M. Guidetti, D. Iniguez, A. Maiorano, F. Mantovani, E. Marinari, V. Martin-Mayor, J. Monforte-Garcia, A. Munoz Sudupe, D. Navarro, G. Parisi, M. Pivanti, Perez-Gaviro, F. Ricci-Tersenghi, J. J. Ruiz-Lorenzo, S. F. Schifano, B. Seoane, A. Tarancon, P. Tellez, R. Tripiccione, D. Yllanes. Ref: The European Physical Journal Special Topics 210, 33 (2012). DOI: https://doi.org/10.1140/epjst/e2012-01636-9

5. JANUS: an FPGA-based System for High Performance Scientific Computing. Janus Collaboration: F. Belletti, M. Cotallo, A. Cruz, L. A. Fernandez, A. Gordillo, A. Maiorano, F. Mantovani, E. Marinari, V. Mart\’in-Mayor, A. Muñoz-Sudupe, D. Navarro, S. Perez-Gaviro, M. Rossi, J. J. Ruiz-Lorenzo, S. F. Schifano, D. Sciretti, A. Tarancon, R. Tripiccione, J. L. Velasco. Ref: Computing in Science & Engineering 11-1, 48-58 (2009). DOI: https://doi.org/10.1109/MCSE.2009.11

6. Simulating spin systems on IANUS; an FPGA-based computer. Janus Collaboration: F. Belletti; M. Cotallo; A. Cruz; L. A. Fernandez; A. Gordillo; A. Maiorano; F. Mantovani; E. Marinari; V. Martin-Mayor; A. Muñoz-Sudupe; D. Navarro; S. Perez-Gaviro; J. J. Ruiz-Lorenzo; S. F. Schifano; D. Sciretti; A. Tarancon; R. Tripiccione; J. L. Velasco; Ref: Computer Physics Communications 178 (3); p.208-216; (2008). Ver también: arXiv:0704.3573. DOI: https://doi.org/10.1016/j.cpc.2007.09.006

7. Ianus: an Adpative FPGA Computer. Janus Collaboration: F. Belletti; I. Campos; A. Cruz; L. A. Fernandez; S. Jimenez; A. Maiorano; F. Mantovani; E. Marinari; V. Martin-Mayor; D. Navarro; A. Muñoz-Sudupe; S. Perez-Gaviro; G. Poli; J. J. Ruiz-Lorenzo; F. Schifano; D. Sciretti; A. Tarancon; P. Tellez; R. Tripiccione; J. L. Velasco. Ref: Computing in Science & Engineering; January/February 2006; Volume 8; N 1; p.41. DOI: https://doi.org/10.1109/MCSE.2006.9

RESEARCH PROJECTS

1. Janus: Ordenador dedicado de nueva generación. Fondos Feder (2007-2013) & Gobierno de Aragón (2012-2013). IP: Alfonso Tarancón Lafita.

2. BFM2003-08532-C03-01. Simulaciones de Monte Carlo de Sistemas Complejos: sistemas fermiónicos, plegamiento de proteínas y ordenadores dedicados. Ministerio de Ciencia y Tecnología – DGI. 01/12/2003 – 30/11/2006. IP: Alfonso Tarancón Lafita.

3. INF2005-CIEN-016. Tarjeta de desarrollo de FPGA-XILINX. Vicerrectorado de Investigación – Infraestructura, Universidad de Zaragoza. 13/07/2005 – 31/12/2005. IP: Alfonso Tarancón Lafita.

COLLABORATORS

INTERNATIONALS

1. Marinari, I. Paga, G. Parisi, F. Ricci-Tersenghi. Università di Roma La Sapienza (Italia)
2. Calore, S. F. Schifano, R. Tripiccione. Università di Ferrara (Italia)
3. Baity-Jesi. Eawag, Dübendorf (Switzerland)
4. Maiorano. Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli studi di Siena (Italia)
5. Yllanes. Chan Zuckerberg Biohub, San Francisco (USA)

NATIONALS

1. Navarro. Departamento de Ingeniería, Electrónica y Comunicaciones & I3A, Universidad de Zaragoza.
2. Gonzalez-Adalid Pemartin, A. Muñoz-Sudupe. Departamento de Física Teórica, Universidad Complutense de Madrid
3. Seoane. LISN – Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay (Francia)

CONTACT

http://www.janus-computer.com

Head of the research line:

Carmen Pérez-Llantada

Researchers:

Carmen Pérez-Llantada
M José Luzón
Ignacio Guillén
Oana Maria Carciu
Miguel Ángel Benítez
Rosana Villares
Miguel Ángel Vela
María de los Ángeles Velilla
Sofía Albero Posac
Ana Cristina Vivas
Alberto Vela

SUMMARY

The resources and computational infrastructure of digital media, including social networks, facilitate the creation and exchange of scientific knowledge not only among researchers in the STEM disciplines but also with the broader public. This line of research focuses on Science 2.0, and examines how science is communicated and disseminated on the Internet and social media, and how scientific knowledge is co-constructed through dialogic interactions within the scientific community and between the researchers and other interest groups (science stakeholders). Along these lines, we investigate why researchers need or want to communicate science in the context of Open Access (OA) and Open Science (OS) policies and how researchers perceive these policies and practices. We also investigate the repertoires of digital genres (written and spoken) that researchers currently use to bring science close to diversified audiences and, by this means, contribute to the democratization of knowledge and the promotion and development of scientific literacy and digital literacy in society.

We carry out quantitative and qualitative analyses to understand the construction of knowledge and knowledge dissemination online, to provide empirical descriptions of researchers’ digital literacy development and to identify the rhetorical strategies that scientists use to reach non-specialized audiences using one or more languages. We are also interested in identifying the STEM researchers’ language and communication needs to address them and enhance their communication skills, one of the key skills for the training of novice and experienced researchers according to the European Commission EURAXESS descriptors. At a methodological level, our research involves the use of digital humanities technologies for the analysis of textual data. Our emphasis is on the use of corpus linguistics, linguistic data processing, and small- and large-scale text mining techniques, as well as computational linguistics and ethnomethodological techniques. All these methods allow us to identify trends in multilingual science communication online and assess the use of language and linguistic repertoires to communicate and disseminate science online with and for society.

In addition, our research aligns with several of the Sustainable Development Goals (SDGs) of the United Nations 2030 Agenda, specifically those proposed by the World Federation of Science Journals. These are global warming and what societies can do to adapt to climate change, mental health, science and global health and the global biodiversity crisis. To do this, we use corpus of electronic texts to carry out descriptive characterizations of different genres for communicating science in digital media, with special attention to phraseological, discursive, pragmatic and rhetorical aspects, as well as features of lexical and syntactic complexity, register and discourse style. We also analyse assemblages of digital genres (for example, genre chains, genre systems, and genre ecologies) and the semiotic resources that researchers can use to disseminate science, including both single and multimodal genres and genres in one or more languages. The outcomes of this research is applied to teaching innovation, advising on scientific policies and language policies, as well as training human resources in the STEM fields in professional communication.

RELEVANT PUBLICATIONS

1. Pérez-Llantada, C. (2023). ‘Help us better understand our changing climate’: Exploring the discourse of Citizen Science. Discourse & Communication, 0(0) (online first).

2. Luzón, M.J. (2023). Multimodal practices of research groups in Twitter: An analysis of stance and engagement. English for Specific Purposes, 70, 17-32.

3. Villares, R. (2023). Exploring rhetorical strategies of stance and engagement in Twitter conference presentations. ESP Today, 11(2), 280-301.

4. M Francisco, MÁ Benítez-Castro, E Hidalgo-Tenorio, JL Castro (2023). A semi-supervised algorithm for detecting extremism propaganda diffusion on social media. Pragmatics and Society, 13 (3), 532-554.

5. Pérez-Llantada, C.; Abián, O.; Cadenas-Sánchez, C.; Carciu, O.; Clemente-Gallardo, J.; Erviti, M.C.; Labayen, I.; León, B.; Ollero, A.; Oses Recalde, M.; Rivera, D.; Vela, A.; Velazquez-Campoy, A.; Villares, R.; Vivas Peraza, A.C. (2022). “Digital Science: Sustainable, transformative and transversal. Final report”, Mendeley Data, V1, doi: 10.17632/2yv5brwxg5.1

6. Vivas-Peraza, A. C. (2022). Engaging the public in science crowdfunding: Scientists calling to action through visual and verbal strategies. Visual Review, 9, 1-15.

7. Carciu, O-M., & Villares, R. (2022). Innovation linked with SDGs: Citizen Science projects to foster competencies for participation in the Digital Society. 8th International Conference on Higher Education Advances (HEAd’22), 1223-1230.

8. Luzón, M.J. and Pérez-Llantada, C. (2022). Digital Genres in Academic Knowledge Production and Communication: Perspectives and Practices. Bristol: Multilingual Matters.

9. Luzón M.J. (2022). “Coronavirus explainers” for public communication of science: everything the public needs to know. In Musolff, A., Breeze, R., Kondo, K. and Vilar-Lluch, S. (eds). Pandemic and Crisis Discourse. Bloomsbury Publishing.

10, Pérez-Llantada, C. (2022). Online data articles: The language of intersubjective stance in a rhetorical hybrid. Written Communication, 39(3), 400-425.

11. Pérez-Llantada, C. & M.J. Luzón (2022). Genre Networks. Intersemiotic Relations in Digital Science communication. New York/Oxon: Routledge.

12. Guillén-Galve, I., & Bocanegra-Valle, A. (eds.) (2021). Ethnographies of Academic Writing Research: Theory, Methods, and Interpretation. (Research Methods in Applied Linguistics Series). Amsterdam/Philadelphia: John Benjamins.

MAIN RESEARCH PROJECTS

1. Digital Language and Communication Training for EU Scientists (DILAN). Erasmus + Programme. Project code 2022-1-ES01-KA220-HED-000086749. (2023-2025). P.I.: Carmen Pérez-Llantada

2. Digital genres and Open Science: An analysis of the processes of hybridization, innovation and generic interdiscursivity (PID2019-105655RB-I00), Plan Nacional I+D+i Ministerio de Innovación y Ciencia, (2021-2024). IPs: M José Luzón y Carmen Pérez-Llantada

3. Ecologies of genres and ecologies of languages: An analysis of the dynamics of scientific communication at local, cross-border and international levels (FFI2015-68638-R MINECO/FEDER, EU) (2015-2020), Plan Nacional I+D+i Ministerio de Economía y Competitividad y Fondos FEDER. IP: Carmen Pérez-Llantada

COLLABORATORS

Vijay K. Bhatia, the Chinese University of Hong Kong (Hong Kong)
Susan Birch Beecas, Université de Bordeux (France)
Dacia Dressen-Hammouda, Université Clermont Auvergne (France)
Christine B. Feak, University of Michigan (USA)
Christoph A. Hafner, City University of Hong Kong (Hong Kong)
Laura-Mihaela Muresan, Bucharest University of Economic Studies (Romania)
Christine B Tardy, University of Arizona (USA)
Pavel Zemliansky, Oslo Metropolitan University (Norway)

CONTACT

digital.science.bifi@unizar.es

Head of the research line:

Gerardo Sanz Sáiz

Researchers:

Javier López Lorente
Ana Carmen Cebrián Guajardo
Pedro Mateo Collazos
Luis Mariano Esteban Escaño
Miguel Lafuente Blasco

SUMMARY

The research of Stochastic Models group (MODES) is structured around two lines of work:

– Analysis of extreme data with applications in Climatology. The main goal is the development of probabilistic and statistical tools to model extreme observations, especially those related with temperature and precipitation.  The analysis of this type of series requires spatio-temporal models, which are developed in a Bayesian framework. The applications focus on the analysis of series in the Ebro valley and Spain but the models can be extrapolated to other regions.

– Predictive models in Medicine. The group has developed statistical models in oncology and gynecology, including online calculators to predict the evolution of patients. We have also built models to be used as decision-aid tools for the management of hospitals. In particular, we have developed a multistate model for predicting hospital and ICU occupancy during a pandemic, such as COVID, which includes a freely available standalone tool. The group also works in the analysis of stochastic models for the logistics of the production process of blood components, in order to minimize expiry rates and maximize freshness.

RELEVANT PUBLICATIONS

1.Bayesian variable selection in Generalized Extreme Value regression: Modeling annual maximum temperature. Castillo-Mateo, J.; Asín, J.; Cebrián, AC.; Mateo-Lázaro, J.; Abaurrea, J. 2023. Mathematics, 11(3) 759.

2.A Multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19. Lafuente, M, López FJ.; Mateo, P.; Cebrián, AC.; Asín, J.; Moler, JA.; Borque, A.; Esteban, LM.; Pérez, A. and Sanz, G. 2023. Heliyon, 9(2) e13545.

3.Testosterone recovery after androgen deprivation therapy in prostate cancer: building a predictive model. Borque, Á; Estrada, F; Esteban, LM; Gil, MJ; Sanz, G. 2022. The world journal of men’s health, 34,588-598.

4.Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragón, Spain. Castillo-Mateo, J.; Lafuente, M.; Asín, J.; Cebrián, AC.; Gelfand, A.; Abaurrea, J.2022. JABES. 27, pp. 487–505.

5.Spatio-temporal analysis of the extent of an extreme heat event. Cebrián, AC.; Asín, J.; Gelfand, A.; Schliep, E; Castillo-Mateo,J; Beamonte, A; Abaurrea, J. 2022. SERRA. 36, pp. 2737–2751.

6.Record tests to detect non-stationarity in the tails with an application to climate change. Cebrián, AC.; Castillo, J.; Asín, J. 2022. SERRA. 36, pp.313–330.

7.Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters. Esteban, J; Castán, B; Castán, S; Chóliz, M; Asensio, C; Laliena, A; Sanz-Enguita, G; Sanz, G; Esteban, LM; Savirón, R. 2022. Entropy, 24, 68.

8.Performance measures of nonstationary inventory models for perishable products under the EWA policy. Gorria, C., Lezaun, M., & López, F. J. 2022. European Journal of Operational Research. 303(3). 1137-1150.

9.Near-Record Values in Discrete Random Sequences. Lafuente, M; Gouet, R; Lopez, FJ; Sanz, G. 2022. Mathematics, 10, 2442.

10.Incorporating a New Summary Statistic into the Min–Max Approach: A Min–Max–Median, Min–Max–IQR Combination of Biomarkers for Maximising the Youden Index. Aznar, R; Esteban, LM.; Sanz, G; Hoyo, R; Savirón, R. 2021. Mathematics, 9, 2497.

11.Analyzing dependence between point processes in time using IndTestPP. Cebrián, AC.; Asín, J. 2021. R JOURNAL. 13 -1, pp. 499 – 515.

12.Long-term spatial modelling for characteristics of extreme heat events JRSS. Series A. Schliep, E.M.; Gelfand, A.; Abaurrea, J.; Asín, J.; Beamonte, MA.; Cebrián, AC.. 2021.Statistics in Society. 84(3), 1070-1092.

13.Forecasting high-frequency river level series using double switching regression with ARMA errors. Cebrián, AC.; Salillas, R. 2021.Water resources Management. 35, pp. 229 – 313.

14.Impact of implementing pathogen reduction technologies for platelets on reducing outdates. Gorria, C., Labata, G., Lezaun, M., López, FJ., Perez Aliaga, AI., & Pérez Vaquero, MÁ. 2020. Vox sanguinis, 115, 167-173.

15.Exact and asymptotic properties of delta-records in the linear drift model. Gouet, R; Lafuente, M; Lopez, FJ; Sanz, G. 2020. JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. P103201.

16.Statistical Inference for the Weibull Distribution Based on d-Record Data. Gouet, R; Lopez, FJ; Maldonado, L; Sanz, G. 2020. SYMMETRY-BASEL. 12.

MAIN RESEARCH PROJECTS

• (2022-2024) Project code: TED2021-130702B-I00. Agencia Estatal de Investigación. Modelización y proyección de récords y extremos medioambientales para evaluación del cambio climático. Aplicación en la cuenca del Ebro y en Pirineos. IP: Gerardo Sanz and Ana Carmen Cebrián.
• (2020-2023) Project code: PID2020-116873GB-I00. Agencia Estatal de Investigación. Modelos estocásticos para estimación y predicción en medicina y extremos medioambientales. IP: F. Javier López and Ana Carmen Cebrián
• (2003-). Project code: E46_20R. Gobierno de Aragón. Modelos Estocásticos. Grupo de investigación de referencia DGA
• (2013-2015) Project code: 2013/0386. Diputación Provincial de Zaragoza Desarrollo de un proyecto de producción y difusión de estadística local. IP: F. Javier López and Gerardo Sanz
• 2013. Project code: 2013/0412. Comercial RAFER S.L. Construcción de modelos estocásticos para predecir la evolución a LMA y la respuesta a tratamiento en pacientes con SMD. IP: F. Javier López

COLLABORATORS