PhD, MSc, BSc
Research challenge and context
In our digital world, the vast datasets that are generated by governments, business and individuals are a rich resource for data-driven innovation – the design of new applications or platforms that use data.
Our solution
Multidisciplinary research undertaken by the Web and Internet Science research group identified societal and technical barriers to data-driven innovation, and ways to overcome them.
Research challenge and context
In our digital world, the vast datasets that are generated by governments, business and individuals are a rich resource for data-driven innovation – the design of new applications or platforms that use data.
Southampton was an early pioneer of the open data movement, showing how transparency of data can revolutionise the way business is conducted, how communities work together and how public services are delivered. Its researchers developed new ways of standardising the presentation of data online so that it can be shared and analysed. These methods underpinned the publishing of datasets through several flagship government projects, including the UK government’s open data portal and the European Data Portal.
The next step was to foster data-driven innovation by transforming access to and use of data across all sectors of the UK economy and beyond.
Our solution
Multidisciplinary research undertaken by the Web and Internet Science research group identified societal and technical barriers to data-driven innovation, and ways to overcome them.
The researchers learned that diverse frameworks and techniques, including big data, sensors and non-public data, were required to solve real-world problems, and that data users needed support to identify and extract value from their datasets. Trust was needed that data processing would be ethical and privacy-preserving. Research into Web Observatories – global resources for holding and sharing datasets and the tools used to visualise and interrogate them – resulted in frameworks to manage the risks related to data sharing.
Analysis of the use of data across 78 portals (the interfaces through which users access datasets) in 35 countries led to the production of guidelines to help designers make portals more user-friendly. Researchers also proposed new frameworks to enable people with non-technical backgrounds in small and medium-sized enterprises (SMEs) to exploit this rich resource.
What was the impact?
Informed by this body of research, Southampton has led the design and delivery of pioneering data incubators, including Open Data Incubator for Europe (ODINE) and Data Pitch. These have contributed to the creation of a European ecosystem for data-driven innovation, supporting digital businesses to fast-track the development of data-driven products through funding, mentoring and access to data.
Since 2006 this has unlocked €38m in funding and created 390 jobs to date across the UK and Europe; this is projected to exceed €115m and 900 jobs. The data incubators have facilitated innovation with data in over 120 organisations, from start-ups and SMEs to public authorities and multinationals – the Met Office and Konica are just some examples.
By stimulating innovation to tackle a range of real-world challenges, these initiatives have resulted in societal as well as economic benefits. For example, they have led to data insights being used to monitor the air quality in cities and develop products to improve it, to help government agencies tackle illegal waste dumping, and to inform winter road de-icing strategies.
Recognised as a global leader in the open data field, Southampton been invited to contribute to policy and help governments design frameworks, codes of practice and standards in areas such as data privacy and anonymisation. For example, its data anonymisation guidance was adapted for Australian legislation in 2017 and the European General Data Protection Regulation in 2020.
Find out more
Talk to our research team and find out more about this work. Professor Dame Wendy Hall, Dr Kieron O’Hara and Dr Thanassis Tiropanis led the research on this project.
Publications
Patino, T., Mestre, R. and Sánchez, S. (2016) Miniaturized soft bio-hybrid robotics: a step forward into healthcare applications. Lab on a Chip, 3626-3630. (doi:10.1039/c6lc90088g).
Mestre, R., Patiño, T., Barceló, X., Anand, S., Pérez-Jiménez, A. and Sánchez, S. (2019) Force modulation and adaptability of 3D-Bioprinted biological actuators based on skeletal muscle tissue. Advanced Materials Technologies. (doi:10.1002/admt.201800631).
Mestre Castillo, Rafael, Patiño, Tania, Barceló, Xavier and Sánchez, Samuel (2018) 3D bioprinted muscle-based bio-actuators: Force adaptability due to training. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 10928 LNAI, Springer, Cham. pp. 316-320 . (doi:10.1007/978-3-319-95972-6_33).
Mestre, Rafael, Patiño, Tania, Guix, Maria, Barceló, Xavier and Sánchez, Samuel (2019) Design, optimization and characterization of bio-hybrid actuators based on 3D-bioprinted skeletal muscle tissue. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 11556 LNAI, Springer Nature Switzerland AG. pp. 205-215 . (doi:10.1007/978-3-030-24741-6_18).
Mestre, Rafael, Palacios, Lucas S., Miguel-López, Albert, Arqué, Xavier, Pagonabarraga, Ignacio and Sánchez, Samuel (2020) Extraction of the propulsive speed of catalytic nano- and micro-motors under different motion dynamics. arXiv.
Arqué, Xavier, Andrés, Xavier, Mestre, R, Ciraulo, Bernard, Arroyo-Ortega, Jaime, Quidant, Romain, Patiño, Tania and Sánchez, Samuel (2020) Ionic species affect the self-propulsion of urease-powered micromotors. Research, [2424972]. (doi:10.34133/2020/2424972).
Kaang, Byung Kwon, Mestre, Rafael, Kang, Dong-Chang, Sánchez, Samuel and Kim, Dong-Pyo (2020) Scalable and integrated flow synthesis of triple-responsive nano-motors via microfluidic Pickering emulsification. Applied Materials Today, [100854]. (doi:10.1016/j.apmt.2020.100854).
Patiño, Tania, Arqué, X, Mestre, R, Palacios, Lucas S. and Sánchez, S (2018) Fundamental aspects of enzyme-powered micro- and nanoswimmers. Accounts of Chemical Research, 2662–2671. (doi:10.1021/acs.accounts.8b00288).
Xuan, M, Mestre, R, Gao, C, Zhou, C, He, Q and Sánchez, S (2018) Noncontinuous super-diffusive dynamics of a light-activated nanobottle motor. Angewandte Chemie (International ed. in English), 6838-6842. (doi:10.1002/anie.201801910).
Mestre, R, Patiño, T and Sánchez, S (2021) Biohybrid robotics: from the nanoscale to the macroscale. Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology, 13 (5), 1-26, [e1703]. (doi:10.1002/wnan.1703).
Mestre, R., Cadefau, N., Hortelão, A.C., Grzelak, J., Gich, M., Roig, A. and Sánchez, S. (2021) Nanorods based on mesoporous silica containing iron oxide nanoparticles as catalytic nanomotors: study of motion dynamics. ChemNanoMat, 7 (2), 134-140. (doi:10.1002/cnma.202000557).
Mestre, Rafael, García, Nerea, Patiño, Tania, Guix, Maria, Fuentes, Judith, Valerio-Santiago, Mauricio, Almiñana, Núria and Sánchez, Samuel (2021) 3D-bioengineered model of human skeletal muscle tissue with phenotypic features of aging for drug testing purposes. Biofabrication, 13 (4), [045011]. (doi:10.1101/2020.06.18.158659).
Guix, Maria, Mestre, Rafael, Patiño, Tania, Corato, Marco De, Fuentes, Judith, Zarpellon, Giulia and Sánchez, Samuel (2021) Biohybrid soft robots with self-stimulating skeletons. Science Robotics, 6 (53), [eabe7577]. (doi:10.1126/scirobotics.abe7577).
Mestre, Rafael, Milicin, Razvan, Middleton, Stuart and Ryan, Matthew (2021) M-Arg: MultiModal Argument Mining Dataset for Political Debates with Audio and Transcripts. University of Southampton doi:10.5281/zenodo.5653503 [Dataset]
Mestre, Rafael, Milicin, Razvan, Middleton, Stuart, Ryan, Matthew, Zhu, Jiatong and Norman, Timothy (2021) M-Arg: multimodal argument mining dataset for political debates with audio and transcripts. 8th Workshop on Argument Mining. 9 pp . (doi:10.18653/v1/2021.argmining-1.8).
Contact
Email: R.Mestre@soton.ac.uk