- From: Sarven Capadisli <info@csarven.ca>
- Date: Tue, 29 Jul 2014 02:51:16 +0200
- To: Linking Open Data <public-lod@w3.org>, SW-forum <semantic-web@w3.org>
- Message-ID: <53D6F004.2040701@csarven.ca>
On 2014-07-29 00:45, Andrea Splendiani wrote: > while I agree with you all, I was thinking: is the lack of reproducibility an issue due to the way results are represented ? > Apart for some fields (e.g.: bioinformatics), materials, samples, experience are probably more relevant and much harder to reproduce. I think that depends on who we ask and how much they care about reproducibility. *IMHO*, the SW/LD research scene is not exactly hard-science. It leans more on engineering and development than following the pure scientific method. Majority of the research that's coming out of this area focuses on showing positive and useful results, and that appears to materialize in some ways like: * My code can beat up your code. * We have something that is ground breaking. * We have some positive results, and came up with a research problem. How often do you come across negative results in the proceedings i.e., some *exploration* which ended up at a dead end? It is trivial to find the evaluation section of a paper often replaced with benchmarks. Kjetil, pointed at this issue eloquently at ISWC 2013: http://folk.uio.no/kjekje/2013/iswc.pdf . Emphasizing on the need to do careful design of experiments where required. In other cases, one practically needs to run after the authors 1) to get a copy of the original paper, 2) the tooling or whatever they built or 3) the data that they used or produced. It is generally assumed that if some text is in a PDF, and gets a go ahead from a few reviewers, it passes as science. Paper? Code? Data? Environment? Send me an email please. I am generalizing the situation of course. So, please put your pitchforks down. There is a lot of great work, and solid science conducted by the SW/LD community. But lets not keep our eyes off Signal:Noise. So, yes, making efforts toward reproducibility is important to redeem ourselves. If you think that reproducibility in some other fields is more relevant and harder, well, then, I think we should be able to manage things on our end, don't you think? The benefit of having the foundations for reproducibility via LD is that, we make it possible to query our research process and output, and introduce the possibility to compare atomic parts of the experiments, or even detect and fix issues. If we can't handle the technicality that goes into creating "linked research", how can we expect the rest of world to get on board? And we are not dealing with a technical problem here. It is blind obedience and laziness. There is absolutely nothing stopping us from playing along with the archaic industry models and publishing methods temporarily (for a number of good and valid reasons), if and only if, we first take care of ourselves and have complete control over things. Publish on your end, pass a stupid fixed copy to the conference/publisher. Then see how quickly the research "paper" landscape changes. As I've stated at the beginning, it all depends on who we ask and how much they care. Do we? If so, what are we going to do about it? -Sarven http://csarven.ca/#i
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Received on Tuesday, 29 July 2014 00:51:48 UTC