The ARC released the composition of the ERA’15 Research Evaluation Committees (RECs) a few days ago. The one relevant to us is the Mathematics, Information and Computing Sciences (MIC) REC. So I was a bit surprised when I looked at it and recognised almost no names.
For those living outside Australia, outside academia, or have their head firmly burrowed in the sand, ERA is the Excellence in Research for Australia exercise the Australian Research Council (ARC, Oz equivalent of the NSF) has been running since 2010. It aims to evaluate the quality of research done at Australian universities. I was involved in the previous two rounds, 2010 as a member of the MIC panel, and 2012 as a peer reviewer.
The ERA exercise is considered extremely important, universities take it very seriously, and a lot of time and effort goes into it. The outcomes are very closely watched, universities use it to identify their strengths and weaknesses, and everyone expects that government funding for universities will increasingly be tied to ERA rankings.
The panel is really important, as it makes the assessment decisions. Assessment is done for “units of evaluation” – the cartesian product of universities and 4-digit field of research (FOR) codes. The 4-digit FORs relevant to computer science and information systems are the various sub-codes of the 2-digit (high-level) code 08 – Information and Computing Sciences.
For most other science and engineering disciplines, assessment is relatively straightforward: you look at journal citation data, which is a pretty clear indication of research impact, which in turn is a not unreasonable proxy for research quality. In CS, where some 80% of publications are in conferences, this doesn’t work (as I’ve clearly experienced in the ERA’10 round): the official citation providers don’t understand CS, they don’t (or only very randomly) index conferences, they don’t count citations of journal papers by conference papers, and the resulting impact factors are useless. As a result, the ARC moved to peer-review for CS in 2012 (as was used by Pure Maths and a few other disciplines in 2010 already).
Yes, the obvious (to any CS person) answer is to use Google Scholar. But for some reason or other, this doesn’t seem to work for the ARC.
Peer review works by institutions nominating 30% of their publications for peer review (the better ones, of course), and several peer reviewers are each reviewing a subset of those (I think the recommended subset is about 20%). The peer reviewer then writes a report, and the panel uses those to come up with a final assessment. (Panelists typically do a share of peer review themselves.)
Peer review is inevitably much more subjective than looking at impact data. You’d like to think that the people doing this are the leaders in the field, able to objectively assess the quality of the work of others. A mediocre researcher is likely to emphasise factors that would make themselves look good (although they are, of course, excluded from any discussion of their own university). Basically, I’d trust the judgment someone with an ordinary research track record much less than that of a star in the field.
So, how does the MIC panel fare? Half of it are mathematicians, and I’m going to ignore those, as I wouldn’t be qualified to say anything about their standing. But for CS folks, citation counts and h-factors as per google scholar, in the context of the number of years since their PhD, is a very good indication. So let’s look at the rest of the MIC panellists, i.e. the people from computer science, information systems or IT in general.
|Name||Institution||years of PhD||cites||h-index|
|Leon Sterling (Chair)||Swinburne||~25||5,800||28|
|Deborah Bunker||USyd||15?||max cite =45|
[Note that Prof Bunker has no public Scholar profile, but according to Scholar, her highest-cited paper has 45 citations. Prof’s Sterling’s public Scholar profile includes as the top-cited publication (3.3k cites) a book written by someone else, subtracting this leads to the 5.8k cites I put in the table. Note that his most cited publication is actually a textbook, if you subtract this the number of cites is 3.2k.]
Without looking at the data, one notices that only three of the group are from the research-intensive Group of Eight (Go8) universities, plus one from overseas. That in itself seems a bit surprising.
Looking at the citation data, one person is clearly in the “star” category: the international member Michael Papazoglou. None of the others strike me as overly impressive, a h-index of around 30 is good but not great, similar with citations around the 3000 mark. And in two cases I can really only wonder how they could possibly been selected. Can we really not come up with a more impressive field of Australian CS researchers?
Given the importance of ERA, I’m honestly worried. Those folks have the power to do a lot of damage to Australian CS research, by not properly distinguishing between high- and low-quality research.
But maybe I’m missing something. Let me know if you spot what I’ve missed.