Oshani, thanks for speaking to me today, and congratulations on your appointment as deputy-chair of WSTNet – I know we are all delighted to have you as part of the senior leadership team.

A. Thanks Ian – it’s a great honour, and I’m really looking forward to it.

Q. So for some background can you tell us how you first got interested and drawn into the Web and Web Science?

A. Well, I actually did my PhD under Tim Berners-Lee at MIT back in 2007 and met a whole group of people like Tim, Danny Weitzner, and Jim Hendler who were engaging with the idea of Web Science. During that time, I was offered the chance to attend a Summer Doctoral Program at the Oxford Internet in 2008.

Q. So did you find this meeting of different viewpoints to simply be a “blue sky” exercise (an entertaining curiosity?) or was it a genuine learning experience?

A. I found the summer doctoral program at Oxford tremendously interesting – mixing viewpoints from Comp Sci, Law, Communications, and many others. I was just starting my PhD back then, and I was probably the most junior student in the mix, so it was very informative to see what kind of web science and related research the other PhD participants were doing. This was not only a source of some great ideas – but also produced a number of working relationships/collaborations that have lasted ever since. I actually met Matt Weber at that first summer school. I also co-authored several papers with some others who attended the summer school through collaborations over the years.

I then spent three months at Southampton WSRI working with Nigel Shadbolt . During that time I worked on a project that subsequently led to my masters thesis at MIT. Collaborations with other WSRI scholars, when they were at MIT, even led to a highly cited paper “ Decentralization: the future of online social networking”  paper that was a pre-cursor to SOLiD – so that work underpins important work that is still progressing today.

Q. This feels like a great advert for WSTNet – how much of this kind of collaboration is still going on?

A. We’d like to be doing more of these collaborative projects, but the challenge is to find common/corresponding funding organisations, not only across regions but also across disciplines. There is no lack of possible collaborations, but interdisciplinary funding/co-ordination remains challenging. But we are working hard to find creative solutions and keep the collaborations going.

Q. WebSci was originally defined as “Interdisciplinary” at its core but has this remained the case or has it transitioned to largely AI/Comp Sci model approaches?

A. As the program chair, program committee member, and senior program committee member of a number of WebSci conferences, I am still seeing submissions from various disciplines (communications, sociology, law, etc) expressing societal problems. Whilst the majority do have a Comp Sci focus (given this is where the tools and the solution space are) I still firmly believe that Comp Sci, whilst a key component, cannot, in of itself be “the answer” to these types of societal problem nor the only approach. WebSci is still interdisciplinary and should firmly remain so.

Q. So to some extent there is a hurdle here of missing programming skills for non CompSci researchers – is there a need for less technical (low code or no-code) tools to be more inclusive? We did have a no code tool produced in the WSTNet by Cardiff University called COSMOS (sadly deprecated now) – perhaps GenAI tools are the new approach to this?

A. Yes, GenAI tools can certainly provide a good support infrastructure for non-CS experts to improve their coding skills. However, these tools should not be used blindly–they have to be careful in the application of the code: what does this code actually do? How can it be debugged/maintained? Whilst the CompSci community is unlikely to simply offer to debug code written by other groups, we could look at how to align these tech/non-tech collaborations so that all parties benefit from the work. Solutions may lie more in exploring novel algorithms from other disciplines for CompSci collaborators whilst providing computational/analytical support for experts from less technical areas. We actually have an upcoming workshop at the WebSci’25 conference, exactly on this topic.

Q. Overall what is your vision for the WSTNet?
A. First and foremost, we need to train the next generation of researchers – I got encouragement and training early on. and we need to pass that on. Being an interdisciplinary researcher is tricky: – promotion is not easy across research/publishing/funding boundaries, and each researcher will generally be based in ONE discipline/department. Each will have a set of the latest/greatest problems, and these may be technical rather than societal. We need more seminars, co-sponsored activities not necessarily to CALL themselves Web Scientists but ultimately to do good quality interdisciplinary research on how the Web acts and interacts with our society.

Within the network, Lab directors continue to work on finding joint grants/funding, and we need this to enable the PhD students to engage in the events so they can benefit from a rich and diverse collaborative network whilst promoting their latest work, papers, and events. Once incentives can be aligned across organisations collaborations fall naturally into place.

We want to see our students work together across cultural and disciplinary boundaries and share their insights, results, and questions with other labs: joint grants will help – social platforms (YouTube channels, etc.) and live events with featured speakers from students up to distinguished/established professors.

As part of passing the torch to the next generation, we need to review our goals and our mission – I’m thinking of events like our last WebSci Dagstuhl manifesto – what are we interested in pursuing? What are the key challenges? How can we adapt to the changing landscape of the Web?

Q. Good point – so what do you see as the new challenges?

A. I guess, first and foremost, the changing nature and availability of data for scientific research. Look at the transition from Twitter → X and the user migration to Bluesky.) We do have the Fediverse, but we now need to be much more aware of where the data is coming from, how reliable it is, and who owns/controls it.

We must offer training to researchers on these new challenges. In an environment of bots/fakes, how much of the available data is even real/valid (not planted), and what are the ownership/copyright issues over obtaining/scraping data? What are the Ethics of using such data? How will we define truth where data may be easily found to confirm any/all conclusions and positions? How will we define data/evidence/truth when video/audible/text can all be generated at will to say whatever is required?

Q. Thanks so much for sharing your views today