submission to LIDA-Turing Mobility and Health Workshop

[GretaTimaite]

I think LIDA-Turing Mobility and Health Workshop would be a great opportunity to present (final?) transport data packs.

Abstract: 30-150 words Deadline: 3 October 2022 Format: hybrid Venue: University of Leeds, UK Event date: 13 October, 2022 (full-day event)

Presentation format is either lighting talk (5 mins) or "regular" presentation (10 mins). What do you think @hulsiejames, @Robinlovelace?

It shouldn't take much time, so I'm happy to write an abstract, if you think it's a good audience to present to.

[Robinlovelace]

I say go for a 10 min presentation, we have lots to say!

[hulsiejames]

Agree with the proposal for a 10 minute talk also. Looks good! I can help propose an abstract too, I know you're busy today @GretaTimaite

[GretaTimaite]

You can draft it if you want @hulsiejames. I'm not writing it today as there's still a month to go, but adding to a TODO list for now.

[hulsiejames]

can you please provide title and abstract (30-150 words)

Please see the current proposed title and abstract below - this currently uses 147 words for the title and abstract.

Any alterations and feedback appreciated!

If you would prefer to edit/comment this through word, you can use the following link. Note that only Greta, Robin and I can edit through this link using our university accounts.

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OpenInfra: Utilising OpenStreetMap for sustainable transport planning

In a post pandemic – high inflation world, active travel modes will become more important due to reduced public transport capacities and increased costs. New policies, investment programs (the Active Travel Fund) and government agencies (Active Travel England) are leading to increased demand for local evidence to better support respective decision-making processes.

The OpenInfra project looks to assess the utility of OpenStreetMap (OSM), an open and free editable map of the entire planet built by volunteers, as local evidence to better support the decision process for local policy provision, and to assist in the prioritisation of upgrading or development of active travel infrastructure. Through the creation of transport infrastructure data packs, the project looks to include value added data with a suite of openinfra package functions that recategorise OSM data into a more insightful categories – for more information, please see: https://github.com/udsleeds/openinfra

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[GretaTimaite]

@hulsiejames, thanks for drafting it. I'm not editing the whole thing just now but here are my initial thoughts/comments:

1. It's great you mention public transport, but health + environment might be more evident reasons to support sust.travelling
2. Great mention of ATF + ATE
3. not clear in the abstract why OSM has been chosen. Why not OS? ie, what are the benefits of OSM (promotes reproducibility, etc)
4. why do we need to add value to OSM. Basically you finish your abstract at the most important point and then tell your reader to learn about it himself/herself. I'm sure this can be written with more nuance.

In general, I'd structure the abstract around:

• what (what is the end goal of the project),
• why (why it's important: a demand for local data-informed evidence)
• how (functions, data packs)

I hope it helps but do not feel obliged to follow the proposed structure if you feel more confident in yours. Good luck and this is a much better draft abstract compared to the one you wrote for the ResCompLeedsCon2022.

[Robinlovelace]

Going to make some tracked changes... in GitHub naturally!

[GretaTimaite]

Has this been submitted @hulsiejames?

[hulsiejames]

Not yet @GretaTimaite - though the deadline isn't for another month, and I did not know if you had any additional thoughts/comments!

I was potentially going to have another attempt at getting the abstract down to 150 words, but with time constraints (and it looks like it would accept the 177 word version) I may just submit as is.

[hulsiejames]

Not yet @GretaTimaite - though the deadline isn't for another month, and I did not know if you had any additional thoughts/comments!

I was potentially going to have another attempt at getting the abstract down to 150 words, but with time constraints (and it looks like it would accept the 177 word version) I may just submit as is.

[GretaTimaite]

Ok, thanks James. I wasn't sure if it was submitted after all those commits or not. Please, if you need any help then tag me explicitly as it can be hard to keep up.

Maybe it's time to start using Projects option on GH to keep a track of everything happening: https://github.com/udsleeds/openinfra/projects/1

Also, don't submit more than 150. It's plain rude and if I was them then I'd reject simply for this reason. Maybe the form does not allow to set a word count below 200 or something but they may have an internal word count system and reject the abstract or cut it at 150 words. I'll have a look at the abstract in due time.

[Robinlovelace]

My bad for going over the word limit, shouldn't be too much hassle to get it back down to size. Also thought it was soon the deadline but now see it's 3rd October, not September, plenty of time!

[hulsiejames]

Abstract has been sumbitted!

[Robinlovelace]

Great work James!

[Robinlovelace]

FYI I just submitted an abstract starting with the following:

Data on active travel is messy. Many interventions are small, and there are hundreds of them in a single authority. Furthermore, interventions to support active travel should be diverse, to support diverse users. It may be relatively easy to sketch a line representing a new cycleway or an area representing a proposed LTN, but it’s hard to develop and maintain a database on active travel infrastructure and planned interventions. To avoid ‘reinventing wheels’, it makes sense to develop a tool for this that is future-proof and nationally scalable.

[hulsiejames]

Is this for the turning mobility too? Looks good!

[Robinlovelace]

Yep : )

[hulsiejames]

The abstract has been accepted! Looking forward to presenting for it next Thursday (Oct 13th) at ITS!

Abstract reminder below:

Investment in active travel modes contributes to tackling climate, health, and cost-of-living crises. New policies, investment programs, and government agencies demand high quality, geographically specific data to ensure effective resource allocation.

OpenInfra explores the potential of open data sources to meet this demand. Specifically, OpenStreetMap (OSM), a free, open, crowdsourced map of the entire world, is explored. We hypothesise that OSM data can support local decision-making processes, and the prioritisation of new active travel infrastructure.

Our findings broadly support, with some limitations, the initial hypothesis. This will be done through comparison of OSM data with official datasets, e.g. Transport for London's Cycling Infrastructure Database. Additionally, we present transport infrastructure data packs aimed at supporting transport planners working for every local authority in England.

Project outputs are open, enabling others to reproduce and adapt our work. Project repository can be found at: https://github.com/udsleeds/openinfra

[GretaTimaite]

Cool, good luck with the presentation 👍🏻

[Robinlovelace]

Great stuff, mine was also accepted...

[Robinlovelace]

Title (just added): Ideas and tools for standardising data on existing and proposed interventions to support walking, wheeling and cycling

Data on active travel is messy. Many interventions are small, and there are hundreds of them in a single authority. Furthermore, interventions to support active travel should be diverse, to support diverse users. It may be relatively easy to sketch a line representing a new cycleway or an area representing a proposed LTN, but it’s hard to develop and maintain a database on active travel infrastructure and planned interventions. To avoid ‘reinventing wheels’, it makes sense to develop a tool for this that is future-proof and nationally scalable. This talk will discuss these issues and how they could be addressed by data science tools to support sustained collection, maintenance and usage of transport infrastructure data, long term.