(Re)Starting at The University of Melbourne

“I am looking for PhD students with topics related to computational urban GIScience” is one of the main pieces of content I have updated on this website. Being back in Melbourne is exciting, and I am keen to sink my teeth in some ideas that have been germinating for a while. Please, spread the word, or get in touch. Note that only students with an outstanding profile from their Masters studies may be eligible for local funding. But if you really see yourself in the profile outlined here, get in touch anyway.

Exploring patterns of individual transcontinental oscillation between Australia and Europe. A subjective study.

The cryptic title hides a prosaic content: I will be wrapping up here in Zurich by the end of the year and I will be returning to the University of Melbourne and the Geomatics group at the Department of Infrastructure Engineering, from January 2016. I am looking forward to rekindling my existing ties in Melbourne and developing new ones, and I hope to continue my collaboration with my amazing Swiss colleagues.

 

And I am looking for some great PhD students interesting in exploring urban GIScience with me…

Information Retrieval. What are the temporal trends?

Part II of series, that started by looking at GIScience (my core interest)

This is, as far as I know, the first publication of temporal trends in Google Metrics.

For the last three years, Google Scholar has been releasing their Google Scholar Metrics. Recently, they released the 2015 batch.

These Metrics provide an insight into the most successful/impactful publication outlets for individual disciplines (and subdisciplines) and also allow one to explore the most cited papers by their h5 index (h5 for a venue/author is the n (number) of papers with at least n citations, in this case for a 5 year period).

There are problems with the way these data are collected (not all venues are monitored, and the coverage may not be 100%, see here). The coverage has been slowly improving over the years. While Computer Science is relatively well covered, some conferences/workshop published in the well respected Springer Lecture Notes in Computer Science series are not monitored by Google and the individual volumes can not be well sorted into disciplines anyway.

Anyway, this project has been running for 3 years now and we can start looking at some trends (without any statistical insights, for this the series are too short). It is worth to note some separation of the journals into tears ( purely visually). Note that this may not say anything about the quality of the venue itself but maybe the audience is smaller/more niche).

It would be worth to compare these trends with the sibling disciplijne of data mining/knowledge discovery, where many venues are used by both communities.

Also note the discussion of the h5 index in here (Vrettas and Sanderson, 2015), suggesting that the size of the venue tends to lead to an over-inflation of its h5index. I would be happy to include additional venues into this, and share data for deeper investigation. I acknowledge the seed list of IR venues from @IR_oldie for this analysis.

I am looking forward to comments!

GIScience Google Metrics trend

References:

Vrettas, G. and Sanderson, M. (2015), Conferences versus journals in computer science. Journal of the Association for Information Science and Technology. doi: 10.1002/asi.23349

Acknowledgment:

The R Hadleyverse for rvest, tidyr, stringr, dplyr and ggvis! Great little problem to learn these!

GIScience in Google Metrics. What are the temporal trends?

This is, as far as I know, the first publication of temporal trends in Google Metrics.

For the last three years, Google Scholar has been releasing their Google Scholar Metrics. Recently, they released the 2015 batch.

These Metrics provide an insight into the most successful/impactful publication outlets for individual disciplines (and subdisciplines) and also allow one to explore the most cited papers by their h5 index (h5 for a venue/author is the n (number) of papers with at least n citations, in this case for a 5 year period).

There are problems with the way these data are collected (not all venues are monitored, and the coverage may not be 100%, see here). The coverage has been slowly improving over the years. GIScience is, however, still only covered in a patchy way. In particular the conferences (GIScience and COSIT, but also SDH and smaller workshops) are not covered as the Springer Lecture Notes are not monitored by Google and the individual volumes can not be well sorted.

Furthermore, some journals from the field are not covered either: JOSIS is not that new anymore, but together with Spatial Cognition and Computation they have troubles to meet at least 100 publications a year so far (see here again for coverage parameters). I assume this is the case for IJLBS as well.

Anyway, this project has been running for 3 years now and we can start looking at some trends (without any statistical insights, for this the series are too short). It is worth to note some separation of the journals into tears ( purely visually). NOte that this may not say anything about the quality of the venue itself (I consider EPB to be an excellent journal with great content, but maybe the audience is smaller/more niche).

It would be worth to compare this with past work of, say, Kemp, Kuhn and Brox (2013) [here], performing a Delphi study of GIScience journals.

Also note the discussion of the h5 index in here (Vrettas and Sanderson, 2015), suggesting that the size of the venue tends to lead to an over-inflation of its h5index. I would be happy to include additional venues into this, and share data for deeper investigation.

I am looking forward to comments!

GIScience Google Metrics trend

References:

Vrettas, G. and Sanderson, M. (2015), Conferences versus journals in computer science. Journal of the Association for Information Science and Technology. doi: 10.1002/asi.23349

Acknowledgment:

The R Hadleyverse for rvest, tidyr, stringr, dplyr and ggvis! Great little problem to learn these!

More kudos for AURIN

It is great to observe from distance how AURIN is growing in recognition in Australia. Yesterday, AURIN became the Merit recipient in the Government category of the Victorian 2015 IAWARDS . Congratulations to all that helped getting this project where it is now – from vision to realisation. And in particular, to all the users!

Defensive wayfinding at COSIT 2015

Can you tell that the route directions you are following are wrong? Can you tell which part of these directions is incorrect? In our recently accepted paper on “defensive wayfinding”, Kai-Florian and I are investigating which kinds of uncertainty in route directions can be detected by wayfinders during wayfinding. Not much work has been done on this topic so far, and we are looking forwad to a lively discussion at COSIT. The uncorrected (accepted) version of the paper is available here: Defensive Wayfinding: Incongruent Information in Route Following.

Analyzing Web Behavior in Indoor Retail Spaces (JASIST paper accepted)

My colleagues Yongli, Flora, Kevin, Mark (all RMIT University) and I have been busy researching indoor user behaviour. We have now got a paper (pre-print) covering the analysis of indoor browsing behaviour in large retail spaces accepted for publication in JASIST (the Journal of the American Society for Information Science, No 1 in Library and Information Science according to Google Scholar Metrics).

From the abstract: “We analyze 18 million rows of Wi-Fi access logs collected over a one year period from over 120,000 anonymized users at an inner-city shopping mall. The anonymized dataset gathered from an opt-in system provides users’ approximate physical location, as well as Web browsing and some search history. Such data provides a unique opportunity to analyze the interaction between people’s behavior in physical retail spaces and their Web behavior, serving as a proxy to their information needs. We find: (1) there is a weekly periodicity in users’ visits to the mall; (2) people tend to visit similar mall locations and Web content during their repeated visits to the mall; (3) around 60% of registered Wi-Fi users actively browse the Web and around 10% of them use Wi-Fi for accessing Web search engines; (4) people are likely to spend a relatively constant amount of time browsing the Web while their visiting duration may vary; (5) the physical spatial context has a small but significant influence on the Web content that indoor users browse; (6) accompanying users tend to access resources from the same Web domains.

This work is supported by the ARC LP Project TRIIBE, and our industry partner – thanks!

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