Accelerating Research Software Understandability Through Knowledge Capture
Summary: Research Software is key to understand, reproduce and reuse existing work in many disciplines, ranging from Geosciences to Astronomy or Artificial Intelligence. However, research software is usually difficult to find, reuse, compare and understand due to its disconnected documentation (dispersed in manuals, readme files, web sites, and code comments) and a lack of structured metadata to describe it. These problems affect not only researchers, but also students who aim to compare published findings and policy makers seeking clarity on a scientific result. In this talk I will present the main research challenges and our recent efforts towards facilitating software understanding by automatically capturing Knowledge Graphs from software documentation and code.
Short bio: Dr. Daniel Garijo Verdejo is a Distinguished Researcher at the Ontology Engineering Group of Universidad Politécnica de Madrid (UPM). Previously, he held a Research Computer Scientist position at the Information Sciences Institute of the University of Southern California, in Los Angeles. Daniel’s research activities focus on e-Science and Knowledge Capture, specifically on how to increase the understandability of research software and scientific workflows by creating Knowledge Graph from their documentation and provenance (i.e., steps, outputs, inputs, intermediate results).
For this talk we will use a hybrid approach: In person (Jack Cole, 1.33) and online, via Teams.
If you wish to attend it would be helpful if you could register on eventbrite to let us know if you intend to attend in person or online
Graduating students and their guests are invited to come along and celebrate with a glass of bubbly.
Mobility Multihoming Duality for the Internet Protocol
In the current Internet, mobile devices with multiple connectivity are becoming increasingly common; however, the Internet protocol itself has not evolved accordingly. Instead, add-on mechanisms have emerged, but they do not integrate well. Currently, the user suffers from disruption to communication on the end-host as the physical network connectivity changes. This is because the IP address changes when the point of attachment changes, breaking the transport layer end-to-end state. Furthermore, while a device can be connected to multiple networks simultaneously, the use of IP addresses prevents end-hosts from leveraging multiple network interfaces — a feature known as host multihoming, which can potentially improve the throughput or reliability. While solutions exist separately for mobility and multihoming, it is not possible to use them as a harmonised solution for the end-host.
This work extended ILNPv6, an engineering solution of Identifier Locator Network Protocol (ILNP) implemented as a superset of IPv6 on the Linux kernel. The existing implementation was extended to harmonise mobility and multihoming. First, the mobility implementation was en- hanced to support rapid and continuous mobility; a comparative analysis against MIPv6 showed superior performance during high rate of handoffs. Second, multihoming was implemented and integrated with mobility; the evaluation with a flexible multi-connectivity scenario with load-balancing showed negligible loss and consistent throughput. Finally, the impact of the combined mobility-multihoming mechanism was evaluated with a real-time video stream application showing continuous uninterrupted real-time video playback at 2160p (4k ultra high definition). Overall, this work has demonstrated that mobility-multihoming duality is possible for end-hosts over IPv6 for existing applications without changing the network infrastructure.
The viva took place on Microsoft Teams on 7/03/2022.
Congratulations to David Letham who has been invited to the Gives Back Awards 2022, on behalf of University of St Andrews Charities Campaign.
David is one of the first winners of the making a difference Award. This new Award comes from students and staff who would like to nominate members of staff who have gone the extra mile within St Andrew’s community and beyond. Whether that be stepping up to help others during exceptional times, showing initiative or making a positive impact on the individuals/communities they have worked with
Enjoy the Ceremony!
SISCO Conference, 5 & 6 February
Ian Gent, Chris Jefferson and Simon Dobson are all presenting at the SISCO conference this weekend. There will be social and networking events which include free food in the medicine cafeteria. We think that these will be nice opportunities for all students, speakers and staff to get to know one other.
You are all invited to these events, both on Saturday and Sunday.
You can get your free tickets to attend and further information on their Facebook page
Very many congratulations to our Emeritus Professor Ian Sommerville who has recently been awarded the 2022 Nancy Mead award for excellence in software engineering education.
The award will be presented at the (virtual) Conference for Software Engineering and Training next month.
This Award goes to individuals who have demonstrated outstanding contributions to software engineering education and training, as well as to the related area of software engineering professionalism. Contributions may include, but are not limited to: service to the community, papers, reports, books, tools, techniques and media for software engineering education, and outstanding practice of teaching that has been witnessed by the community at large. Contributions should have had an influence over an extended period of time at the international level. Contributions to software engineering itself (peer-reviewed research or practice) should be mentioned in a separate section of any nomination, but having made such contributions is not necessary in order to receive this award.
Well Done Ian!
As part of the schools Distinguished Lecture Series we look forward to welcoming Prof. Giovanna Di Marzo Serugendo on Tuesday 9 November.
Prof. Giovanna Di Marzo Serugendo received her Ph.D. in Software Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 1999. After spending two years at CERN (the European Center for Nuclear Research) and 5 years in the UK as Lecturer, she became full professor at the University of Geneva in 2010. Since 2016, she is the Director of the Computer Science Center of the University of Geneva, Switzerland. She has been nominated in 2018 among the 100 digital shapers in Switzerland. Her research interests relate to the engineering of decentralised software with self-organising and emergent behaviour. This involves studying natural systems, designing and developing artificial collective systems, and verifying reliability and trustworthiness of those systems. Giovanna co-founded the IEEE International Conference on Self-Adaptive and Self-Organising Systems (SASO) and the ACM Transactions on Autonomous Adaptive Systems (TAAS), for which she served as EiC from 2005 to 2011.
This event will be held on Teams with further details to follow.
Can Language Models be Weak Annotators
We are happy to have Phong Le, from Amazon, talk on Teams on Wed 3 March at 12 noon on Teams.
Deep language models e.g. BERT and GPT3 are the breakthrough in Natural Language Processing in the last 3 years. Being trained on massive raw text data, they capture useful priors for several tasks such as syntactic parsing, information extraction, and question answering. Moreover, they are capable of answering factual and commonsense cloze questions such as “Dante was born in _____”. In this talk, I will firstly give an overview about what language models “know”. I will then present our work on exploiting their knowledge as weak supervision for a specific task called relation classification.
Relation classification, the identification of a particular relation type between two entities in text, requires annotated data. Data annotation is either a manual process for supervised learning, or automated, using knowledge bases for distant learning. However, both methodologies are costly and time-consuming since they depend on intensive human labour for annotation or for knowledge base creation. Using language models as annotators, on the contrary, is very cheap but the annotation quality is low. We hence propose NoelA, an auto-encoder using a noisy channel, to improve the accuracy by learning from the low quality annotated data. NoelA outperforms BERT and a bootstrapping baseline on TACRED and reWIKI datasets.
Bio: I’m an applied scientist at Amazon Alexa. Before that, I was a tenure-track research fellow at the University of Manchester. I did a postdoc with Ivan Titov at the University of Edinburgh, and got a PhD from the University of Amsterdam under the supervision of (Jelle) Willem Zuidema. I’m interested in neural networks and deep learning. My current work is to employ them to solve natural language processing tasks such as entity linking, coreference resolution, and dependency parsing. I’m also interested in formal semantics, especially learning semantic parsing.
For more details, please visit my homepage https://sites.google.com/site/lephongxyz/
Please note the session will not be recorded, to preserve the like-for-like nature of physical seminars and also avoid any privacy/rights issues.
- When: 3rd March 2021 12:00 - 3rd February 2021 13:00
- Format: Seminar
Abstract: Have you been frustrated by trying to use someone else’s code which is non-trivial to install? Have you tried to make supplementary code for your paper to be easily accessible for the reader? If so, you certainly know that this may require non-trivial efforts. I will demonstrate some tools that may help to create reproducible computational experiments, and will explain which skills will be needed to use these tools. The talk will demonstrate examples in Python and R runnable in Jupyter notebooks. You are welcome to bring your laptop to try these examples online. No prior knowledge of programming is required.
- Templates for reproducible experiments in GAP, Python and R
- Code4REF guidance on recording research software in Pure
- The Laser Interferometer Gravitational-Wave Observatory (LIGO) demos
- Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks PLOS Computational Biology paper by Adam Rule, Amanda Birmingham, Cristal Zuniga, Ilkay Altintas, Shih-Cheng Huang, Rob Knight, Niema Moshiri, Mai H. Nguyen, Sara Brin Rosenthal, Fernando Pérez and Peter W. Rose
- Hidden REF announcement
- When: 11th February 2020 15:00 - 16:00
- Where: Phys Theatre C
- Format: Talk