Open Tech Calendar

DisCOVER: Data as an Artefact

Data as an artefact
Seminar abstract

The data evolution provided innovative opportunities for growth through multiple analytical applications in decision-making but also a large number of social, technical and ethical concerns. Data as an artefact is comprised of various characteristics, attributes and aspects that could assist in defining measurements of quality control, sharing agreements as well as policies, standards and protocols for access control. Understanding these data characteristics is essential for individuals and organisations to realise new ways of value creation and how to avoid data sharing issues. This presentation will highlight these topics around data, and the associated challenges and explore how the society could deal with them.

Dr Konstantina Spanaki, Loughborough University
Lecturer at the School of Business and Economics and a member of the Centre for Information Management at Loughborough University.

Seminar date/time/location
28 Feb 2020, 12:00-13:00
Information School RC204

https://www.eventbrite.co.uk/e/discover-data-as-an-artefact-tickets-91794446661

https://www.eventbrite.co.uk/e/discover-data-as-an-artefact-tickets-91794446661

Fri 28th Feb 2020 12:00pm (Europe/London)

Fri 28th Feb 2020 1:00pm (Europe/London)

changed

Europe/London

changed

No

Yes

DisCOVER: Innovation and ICTs

Innovation and ICTs
Presentation 1
Where the Global meets the Local – Unpacking the Multiple Spaces of Innovation Hubs

Seminar abstract
This research studies innovation hubs as part of a wider phenomenon of innovation for development. Innovation hubs are collaborative spaces for entrepreneurs that include aspects of coworking, incubators, innovation centres and makerspaces. Despite the lack of clarity of what
impact they have, hubs have been spreading in the Global North and Global South, funded and promoted by international agencies and local governments. Consequently, they are expected to create successful ventures, contribute to job creation and innovation development. My research critically evaluates the discourses of innovation for development and examines the implications of innovation hubs for beyond the mainstream development perspectives, drawing upon two case studies of innovation hubs in Zambia and the UK respectively. As such, I focus on how individuals participating in hubs perceive themselves in innovation, and how social, historical and structural forces shape these perceptions.
Dr. Andrea Jimenez. Lecturer in Information Management, Information School, The University of Sheffield

Presentation 2
An investigation of smart transportation system (STS) data integration within Chinese cities: A socio-technical perspective

Seminar abstract
The study aims to explore the challenges and opportunities of initiating a data-integrated smart transportation system application in the context of China’s new-type urbanisation from a socio-technical system perspective. To achieve this aim, this study adopted a qualitative, interpretative, single case study methodology, and provides both theoretical and practical implications of initiating future STS solutions. It provides an enhanced theoretical understanding of using a socio-technical approach to examine the challenges and opportunities that are likely to be faced with the initiation of future STS solutions. It also delivered practical guidance for smart city practitioners to initiate more citizen-focused, value co-created and sustainable STS solutions.


Jun Zhang. PhD candidate, Information School, The University of Sheffield

Seminar date/time/location
7 Feb 2020, 13:00-14:00
Information School RC204

https://www.eventbrite.co.uk/e/discover-innovation-and-icts-tickets-91796962185

https://www.eventbrite.co.uk/e/discover-innovation-and-icts-tickets-91796962185

Fri 7th Feb 2020 1:00pm (Europe/London)

Fri 7th Feb 2020 2:00pm (Europe/London)

changed

Europe/London

changed

No

Yes

Research Seminar - Extracting actionable knowledge from healthcare policies

29 November 2019 12:00-13:00. Vanessa Lopez, IBM.

Information School level 2: Room 204.

"Extracting actionable knowledge from healthcare policies".

Abstract

The abundance of digital information gives an unprecedented opportunity to use data science in domains such as health and social care. However, the real value of the data is in the information and knowledge that we are able to surface and materialise. Knowledge Graphs (KGs) emerged as a unifying technology that facilitates the aggregation and representation of data from multiple and diverse data sources, both inspired by, and influencing, research in areas such as AI, cognitive computing, the Semantic Web, Search, Question Answering and Information Extraction. In this talk, I will provide a perspective from my journey and experience in adopting research in KGs and related areas to address significant problems in the healthcare industry through two use cases.
The first scenario, Fraud, Waste and Abuse in healthcare, accounts for financial loses in the tens of billions of dollars each year in the US, which limits the amount of funding available to those with legitimate needs. Regulations around compliance are described in text policies, which investigators have to review and refer to in an investigation case for further recovery actions. This is a labour-intense task, the sheer volume of claims and policies to review leads to poor understanding and coverage to prioritize investigations based on the likelihood of (money) recovery from inappropriately paid claims. The aim is to support investigation units identifying improper payments for unnecessary services, services exceeding the permitted unit limitations, or services that should not be billed separately on claims submitted for reimbursement by medical providers.

The second scenario is the delivery of care. Care professionals need to quickly dig through multiple sources to find information about patients. Furthermore, the high volume of (unstructured) case notes written by care professionals for patients receiving multiple services makes it easy to overlook what is really important. The goal is to provide insights from large volumes of unstructured notes to support informed decision making.

KGs combined with natural language, machine learning and semantic reasoning techniques allows us to capture actionable knowledge from policy text to identify improper payments, as well as from unstructured health records (case notes) to answer complex user information needs, and for better suggestions and predictions to be derived from diverse data. The challenges are still plentiful: to validate the value of cognitive systems in providing actionable insights that ultimately lead to better outcomes for individuals, to empower domain experts to co-reason with the system, and for systems to continuously learn from the actual practice of care professionals.

Bio

Vanessa Lopez is a researcher scientist at IBM Research Ireland since 2012, where she investigates AI solutions for integrated healthcare. Her research combines semantics, natural language and learning to create applications that support care professionals taking informed patient-centric decisions, which received the 2017 US-Ireland Research Innovation Award. She is currently the team lead on a project that extracts knowledge from healthcare policies to support detecting fraud, waste and abuse on claim data. Prior to that she was a research associate at KMi (Open University) from 2003, where she built pioneering prototypes for Natural Language interfaces over Linked Data and obtained a PhD. She graduated with a master’s degree in computer engineer from the technical university of Madrid (UPM). Her current research interests are to investigate how technology can be made “smarter” to better understand human needs and to support us, as a society, to target complex problems. In particular, using knowledge graphs as a unifying technology that facilitates capturing, aggregating and interpreting knowledge from diverse data sources, both structured and unstructured. She has participated actively in several EU projects, PC committees and chairing, and co-authored more than 50 publications in high impact conference and journals, with over 3000 citations.

https://www.eventbrite.co.uk/e/research-seminar-extracting-actionable-knowledge-from-healthcare-policies-vanessa-lopez-tickets-77140620673

https://www.eventbrite.co.uk/e/research-seminar-extracting-actionable-knowledge-from-healthcare-policies-vanessa-lopez-tickets-77140620673

Fri 29th Nov 2019 12:00pm (Europe/London)

Fri 29th Nov 2019 2:00pm (Europe/London)

changed

Europe/London

changed

No

Yes

Research Seminar - Dr Styliani Kleanthous, Open University of Cyprus.

22 October 2019 12:00-13:00. Dr Styliani Kleanthous, Open University of Cyprus.

Information School level 3: Digital Media Lab rm 324.

"Fairness in Proprietary Image Tagging Algorithms".

Abstract

Image analysis algorithms have become indispensable in the modern information ecosystem. Beyond their early use in restricted domains (e.g., military, medical), they are now widely used in consumer applications and social media enabling functionality that users take for granted.
Recently image analysis algorithms, have become widely available as Cognitive Services. This practice is proving to be a boon to the development of applications where user modeling, personalization and adaptation are required. But while tagging APIs offer developers an inexpensive and convenient means to add functionality to their creations, most are opaque and proprietary and there are numerous social and ethical issues surrounding their use in contexts where people can be harmed. In this talk, I will discuss recent work in analyzing proprietary image tagging services (e.g., Clarifai, Google Vision, Amazon Rekognition) for their gender and racial biases when tagging images depicting people [1]. I will present our techniques for discrimination discovery in this domain, as well as our work on understanding user perceptions of fairness [2]. Finally, I will explore the sources of such biases, by comparing human versus machine descriptions of the same people images [3].

[1] Kyriakou, K., Barlas, P., Kleanthous, S., & Otterbacher, J. (2019, July). Fairness in Proprietary Image Tagging Algorithms: A Cross-Platform Audit on People Images. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 13, No. 01, pp. 313-322).

[2] Barlas, P., Kleanthous, S., Kyriakou, K., & Otterbacher, J. (2019, June). What Makes an Image Tagger Fair?. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (pp. 95-103). ACM.

[3] Otterbacher J., Barlas, P., Kleanthous, S., Kyriakou, K. 2019.How Do We Talk About Other People? Group (Un)Fairness in Natural Language Image Descriptions. In Seventh AAAI Conference on Human Computation and Crowdsourcing (HCOMP).

Bio

Styliani Kleanthous Loizou (female, Ph.D., University of Leeds, UK) is a research scientist at the CyCAT, Open University of Cyprus as well as the Research Centre on Interactive Media, Smart Systems and Emerging Technologies (RISE). Styliani’s main research interests and expertise are concentrated in the area of User and Community Modeling, Personalization and Adaptive Systems. She specializes in exploiting psychological and social theories for modeling user preferences, for designing intelligent interaction and adaptive user support. She has published over 25 papers in journals and scientific conferences, co-organized a number of international workshops and has given numerous presentations. Since 2004 she has been involved in different UK and EU-funded research projects for establishing requirements, modeling users and providing adaptive support for collaboration, learning, medical data analysis and identifying innovation networks.

https://www.eventbrite.co.uk/e/research-seminar-dr-styliani-kleanthous-open-university-of-cyprus-tickets-75634935127

https://www.eventbrite.co.uk/e/research-seminar-dr-styliani-kleanthous-open-university-of-cyprus-tickets-75634935127

Tue 22nd Oct 2019 12:00pm (Europe/London)

Tue 22nd Oct 2019 1:00pm (Europe/London)

changed

Europe/London

changed

No

Yes

Research Seminar - Prof. Robert Davison, City University of Hong Kong

Monday, November 4, 2019, 10:00-11:00, Regent Court RC 204

Reflections of an IS Career Researcher - Prof. Robert Davison, City University of Hong Kong

Prof. Davison's published work well exceeds 200 papers in prestigious academic journals and conference proceedings. In this seminar, he will provide some highlights of his research on knowledge management and the use of information systems within primarily Chinese organisations and SMEs, with a focus on the most interesting and important aspects.

https://www.eventbrite.co.uk/e/research-seminar-prof-robert-davison-city-university-of-hong-kong-tickets-75122053083

https://www.eventbrite.co.uk/e/research-seminar-prof-robert-davison-city-university-of-hong-kong-tickets-75122053083

Mon 4th Nov 2019 10:00am (Europe/London)

Mon 4th Nov 2019 11:00am (Europe/London)

changed

Europe/London

changed

No

Yes

Dr. Ivan Palomares Carrascosa (University of Bristol) - Personalised Recommendation and Decision Support for Wellbeing and Healthy Living

Bio: Dr. Palomares Carrascosa completed his PhD in Computer Science (nationally awarded in Artificial Intelligence), with the Universities of Jaén and Granada (Spain). Subsequently, between 2014-2017, he has been a research associate, research fellow and senior engineer with Ulster University (UK) and Queen's University Belfast (UK). He is currently a Lecturer with the Department of Computer Science at UoB.

His main research interests and current activities revolve around the following topics/problems:
Decision Making under Uncertainty (predominantly of fuzzy and linguistic nature).
Multi-Criteria, Collective and Consensus-driven Decision Making.
Intelligent Decision Support Systems
Recommender Systems: Multi-View Data Fusion Strategies, Group Recommender Systems and Applications (tourism, smart cities, digital health...)
Preference Modelling and Intelligent Aggregation Methods.
Collaborative Planning and Decision-Making with Autonomous Intelligent Systems.
Applications of Fuzzy Decision Making and Aggregation (autonomous systems, cyber-security, energy planning, ...)

https://www.eventbrite.co.uk/e/research-seminar-dr-ivan-palomares-carrascosa-university-of-bristol-personalised-recommendation-and-tickets-66447200365

https://www.eventbrite.co.uk/e/research-seminar-dr-ivan-palomares-carrascosa-university-of-bristol-personalised-recommendation-and-tickets-66447200365

Tue 3rd Sep 2019 12:00pm (Europe/London)

Tue 3rd Sep 2019 1:00pm (Europe/London)

changed

Europe/London

changed

No

Yes

Research Seminar - The Intelligence of Things

Description
29 April 2019 - 1pm - The Intelligence of Things
Dr Mercedes Bunz, Kings College London
RC204 - Information School

Artificial intelligence – data analysis and machine learning - drives many internet of thing devices from the speaking Siri on our phones to self-driving cars or smart cities. Devices are tracking and tracing their users and communicating with them, processing data and learning about their environment. In her talk, Mercedes will analyse how the agency of technology introduced by intelligent things is currently negotiated. Using critical discourse analysis, the first step will be to contrast technologies that are making things ‘intelligent’ with the way tech companies but also the media address this intelligence. In her second step, she will then focus on the potential of things which that sense their environment, which they offer through their data.

Mercedes Bunz is Senior Lecturer in Digital Society at the Department of Digital Humanities, King's College London. She came to London in 2009 to work as the technology reporter of The Guardian. Her research explores how digital technology transforms knowledge and with it power; a question she explores currently specifically regarding medical knowledge with the Wellcome Trust grant for the project ‘Public data, private collaborator: will machine learning relocate medical knowledge?’ Recent publications: The Internet of Things (Polity 2017) co-published with Professor Graham Meikle, and the small Open Access publication Communication with Finn Brunton (University of Minnesota Press 2019), in which they discuss how contemporary communication puts us not only in conversation with one another but also with our machinery.

https://www.eventbrite.co.uk/e/research-seminar-the-intelligence-of-things-tickets-59892416831

https://www.eventbrite.co.uk/e/research-seminar-the-intelligence-of-things-tickets-59892416831

University of Sheffield Information School

Our mission is to empower people, organisations and society to use information to shape and influence an increasingly dynamic and complex world.

The Information School at The University of Sheffield is a thriving community of students, educators and researchers dedicated to the study and advancement of the information field and its professions. Our field is characterised by its distinctive, interdisciplinary focus on the interactions between people, information and digital technologies. It has the ultimate goal of enhancing information access, and the management, sharing and use of information, to benefit society. Good information empowers people and enriches their lives. Expertise to use, design and manage information products, services and systems effectively has never been more important than today, in our increasingly fast-moving and complex world.

The School has been at the forefront of developments in the information field for more than fifty years. We are recognised as the leading school of our kind in the UK, with an international reputation for the quality of our teaching and research, and for the achievements of our graduates. Our research is world-leading and we achieved the highest possible grade in every one of the Research Assessment Exercise (RAE) evaluations of research quality in UK universities since these began in 1989.

We achieved top positions in the Research Excellence Framework (REF) 2014 for research environment and for the impact of our research, based on the combined 4* (world-leading) and 3* (internationally excellent) categories. The results show that 100% of our research environment was judged to be of world-leading quality and 100% of our research impact was judged as world-leading or internationally excellent. Through our research we seek to make a significant intellectual contribution to advancing knowledge in our field, but also to impact on the practical management and use of information.

Information science is a multidisciplinary and interdisciplinary subject. Our staff backgrounds and research reflect influences from computing, health, chemistry and different arts and humanities and social sciences disciplines, as well as experience from professional practice in information roles. We have particular expertise in information and knowledge management, information systems, libraries and the information society, information retrieval, health informatics, data science and chemoinformatics. We run a vibrant doctoral programme which attracts students from many different countries to work with us in all of these areas.

Students who come to study with us at the Information School are an integral part of our research culture. The School is their home and we pride ourselves on the friendliness and helpfulness of staff. We offer students an outstanding academic education through a wide range of taught postgraduate degrees which embed the principles of research-led teaching. Students joining any of our degree programmes will develop a critical understanding of current issues in library and information management and will benefit from being taught by staff who are undertaking leading-edge research and who have many links with industry. As part of our mission to provide world-quality university education in information, we aim to inspire and help our students to pursue their highest ambitions for their academic and professional careers.

http://www.sheffield.ac.uk/is

Mon 29th Apr 2019 1:00pm (Europe/London)

Mon 29th Apr 2019 2:00pm (Europe/London)

changed

Europe/London

changed

No

Yes