Research Grant Data in the Griffith University Research Hub

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Video in TIB AV-Portal: Research Grant Data in the Griffith University Research Hub

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Title
Research Grant Data in the Griffith University Research Hub
Subtitle
A case study on use of the ANDS Research Grant API
Alternative Title
Research Grant Data at Griffith University
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Release Date
2015
Language
English

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Abstract
Jan Hettenhausen presents Case study: Griffith University’s use of the API to pull in grant records from RDA for Griffith researchers to cover the period where the researchers were not at Griffith. Explore the new Research Data Australia Grants and Projects portal Research Data Australia aggregates: 1. research grant information supplied by multiple funders - currently ARC and NHMRC 2. research project information supplied by some of our data contributors.
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so yeah I work in Griffith University and II research services and a while ago we use the Anne's research grant API to improve the data that we present in the griffins university research hub so the research hub is our publicly facing researcher profile system and we build
that for two main purposes one to make Griffith research more discoverable to show what we're doing and the other one to give researchers a profile that they can use for their own purposes that you know they can share that shows their work individually and to give a bit of background the research hub is bill using VEVO which I serve semantic web application and it's becoming quite popular this there's a large number of universities worldwide that build their research a profile systems based on this it came from Cornell University originally so this is a huge uptake in the u.s. in particular and as a semantic web application it has a couple of very nice benefits for this sort of purpose and one is that it provides a very rich ontology to model information about researchers research related activities organizations such as institutes schools groups and in terms of activities we can model publications grants and other research output and of course it's also easy to add the party or your own ontology is to add even more data to this now when we develop the research hub one of the main aspects that we wanted to cover was that people would
not have to maintain their profiles themselves and so in that spirit we try to get as much data as possible from various enterprise systems that Griffith in external systems if available and so the end at the moment research has really only have to add the photo if they want one a short bio say statement and maybe a research statement and everything else including academic degrees employment history publications grants supervision and so on gets drawn from enterprise systems that we get the same information about institutes groups and schools how have one problem that we came across was that enterprise systems were at some point billed for a specific purpose and that was usually not that the dart would be displayed publicly and for a lot of the data that's not a huge issue publication records are fairly standardized so we didn't have any problems there but grant information in particular was not very well covered in our systems sometimes just because we weren't the managing organization so if things changed later on in terms of titles and amounts and whatnot that wasn't necessarily reflected in our systems and the other reason is that we didn't necessarily need descriptions and whatnot for the reporting purposes the systems were built for so for the research up we identified two business cases where we could use external grand
data and really add some value to the research hub and one was to improve data on existing grains get better descriptions get full funding amounts like the the total grant amount and not just their share that Griffith University got from it and the other business case was that well we knew about grants that at some affiliation with Griffith we didn't know anything about brands that researchers had while they were not at Griffith University and so adding that information became quite important because well it doesn't showcase any Griffith research it is an important part in the biography of our researchers and it gives a much more complete picture especially because we do have historic information about publications and what also not hoping the Grands lift a gap that that many people were sort of eager to close and again we didn't want people to enter this information manually so getting as much of that done automatically as possible was and gone and this is where the ends research grant APR I came in and yes that in the previous talks it
draws from the same data sources as the recipie Australia portal and so it has very comprehensive information especially about a SC and NHMRC grants and it also provides us with a very nicely cleaned up version of this grant information so information that is maybe not well captured in in a standardized vocabulary in the the source data was actually cleaned up and is now provided at a very nice form and the API is based on solar which is a very simple to use very nice and very well documented enterprise search engine and so using this data was actually quite easy for us so for the first business case we didn't actually have to do very much we could basically look up grants based on their grant rd and the
funding body granddaddy's necessarily unique across funding bodies but doing this lookup was quite easy and so we would get back the record as a JSON formatted record and all we really had to do was map those fields to our idea for Kira Larry and do a few related lookups for people in our database I brought up to to link it up properly but all that all it was a very very easy process and um well we did this work quite a while ago so about a year the half I think most of it orbit long run and initially a lot of the text fields still contained a lot of the actual information in terms of funding amounts and what more than we did a fair bit of text processing to extract it as well nowadays um and has done a lot of work on improving this and so we're now getting a much cleaner version of the data so whoever wants to get into this area now and use this information is in a really good position to get very nice and clean data from this the second business case was a lot more difficult so we just heard about research
identifies it's still very difficult to get that information for our researchers at the moment and orchid is not very common yet then we don't get orchid identifies from the API or from the funding bodies so what we had to do to get historic grounds for researchers that had nothing to do miss Griffith was we had to come up with a way of matching researchers by name and for that we build a two-stage scoring function one simply looked at name similarity and gave us some idea whether two names could be referring to the same person and we've put a lot of empirical work into that because sometimes people go by a preferred name sometimes by the actual first name some people always include the middle name some people doing so that's a lot of work to do about that and then we still have the problem or have the problem that names are not unique and so we the second school that was based on the fields of research people published in and we have very good information about that in the research herb so we could build a portfolio of four codes that people had published in previously and we just went by the assumption that if they had a grant in the past that had a certain for code that they would have at least one publication that have that foot boat as well yeah then we had to implement some additional handling for edge cases where brands were actually managed by Griffith that we had information about them but people were different institutions and still attached to them and linking all that up but that was all relatively easy once we have the linking up and running well I can't actually give any numbers about how well we're doing empirically it worked quite well and in practice over the last one and a half years I think we had about two or three false positives with people and informed us that the data was incorrect and we built in functionality to manually add and remove grants but still automatically ingest the data and yeah so both of these cases were very successful and that was largely thanks to how easily the ants API was for us to access into use and yeah I thought to wrap it up I quickly put up some links to the systems
involved the verse was our research hub the second one for those who are interested in to may not know about it already that's the vball project which is definitely worth a look for everyone who's interested in getting it as a space of researcher profile systems the last one is the documentation to the ants API and as it's since it's based on solar there's a lot of additional resources people on the web and yeah
that's all from me
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