Zzzoot

As reported in Heather Morrison's blog. The Imaginary Journal of Poetic Economics .

I am following with a sense of detached fascination UBC researcher Dr. Rosie Redfield's saga of her quest to get her CIHR funded article published in a scientific journal and also made available Open Access . While her blog is not one dedicated to Open Access but instead to her research (" Thinking about our research into the mechanism, function and evolution of DNA uptake by Haemophilus influenzae and other bacteria "), it is clear that she is spending more time and accruing more frustration dealing with this particular issue than she would want to be, or should be... Update: 2008 Nov 12 : It seems that the Dr. Redfield has given up on Elsevier, and has decided to stop publishing articles with this publisher: " ... I won't be submitting to any Elsevier journals in the future ."

This Oct 14 is Open Access Day and the 5th publishing anniversary of the first PLoS journal, so the PloS and others are celebrating both with a number of events, T-shirts, buttons , blog competition, flyer , downloadable posters, bookmark, etc: Spread the word - downloadables, creatables, educational resources T-shirts, buttons and posters - freebies (No T-shirts left :-( ) Participants from around the world organizing large and small local events PS. I wonder if they will be releasing the T-Shirt designs with a Creative Commons license, so anyone can print a T-shirt?

As reported on the Science Blogging 2008: London forum , this clever challenge was announced at the London Science Blogging Conference August 30 2008. Related: Good summary of Timo Hannay 's closing sum-up of the conference and the same blog's ( Humans in Science ) entry on the conference proper.

I Survived the Large Hadron Collider ;-)

The following excerpt from an ad for Scientific Data Management Specialist suggests it bodes well for the prospects of this (relatively) nascent profession: Processing, soliciting, and providing assistance with data submissions for scientific data from genome sequencing and genotyping experiments into existing databases , analysis pipelines and associated data flows. Developing and improving the infrastructure supporting these systems. Required Skills Formal Education PhD Scripting experience in perl or related language Experience with SQL Experience with LINUX/UNIX Ability to use Microsoft Excel and related applications Proven record solving related problems Desired Skills Knowledge of genetics, especially human genetics Experience with large data sets XML/XSLT and related web based tools Experience with array data, especially expression or genotyping data C/C++ Experience with grid computing (LSF,SunGrid, etc.) QA filtering of genotype data (HWE, non-Mendelian segregation)

I am excited at the release of Katta , a technology built on Lucene , Zookeeper and Hadoop allowing for Lucene indexes to be distributed across a number of nodes for distributed & fault tolerant search. Note that it does not create the indexes, simply deploys existing indexes onto this infrastructure.

Research and Advanced Technology for Digital Libraries 12th European Conference, ECDL 2008, Aarhus, Denmark, September 14-19, 2008. Lecture Notes in Computer Science. Volume 5173: Research and Advanced Technology for Digital Libraries. Ed. Birte Christensen-Dalsgaard, Donatella Castelli, Bolette Ammitzbøll Jurik, Joan Lippincott. Table of Contents: George Buchanan, Jennifer Pearson. Improving Placeholders in Digital Documents Ying Jiang, Hui Dong. Towards Ontology-Based Chinese E-Government Digital Archives Knowledge Management Christoph Becker, Miguel Ferreira, Michael Kraxner, Andreas Rauber, Ana Alice Baptista, José Carlos Ramalho. Distributed Preservation Services: Integrating Planning and Actions Eld Zierau, Anders Sewerin Johansen. Archive Design Based on Planets Inspired Logical Object Model Manfred Thaller, Volker Heydegger, Jan Schnasse, Sebastian Beyl, Elona Chudobkaite. Significant Characteristics to Abstract Content: Long Term Preservation of Information Khasfariyati Razi

The Industry Canada minister accepted (Sept 2 2008) recommendations from the Science, Technology and Innovation Council on the sub-priorities of the four priority areas identified in the 2007 Science and Technology (S&T) Strategy ( The State of Science & Technology in Canada , 2006, Council of Canadian Academies ). The recommended sub-areas are: S&T priority: Environmental science and technologies Sub-priorities : Water (health, energy, security); cleaner methods of extracting, processing and using hydrocarbon fuels, including reduced consumption of these fuels S&T priority: Natural resources and energy Sub-priorities : Energy production in the oil sands; Arctic (resource production, climate change adaptation, monitoring); biofuels, fuel cells and nuclear energy S&T priority: Health and related life sciences and technologies Sub-priorities : Regenerative medicine; neuroscience; health in an aging population; biomedical engineering and medical technologies S&T p

The previously reported "Review of the National Innovation System Report - Venturous Australia" -- interestingly and surprisingly -- includes a whole section entitled " Innovation in Government ". Its recommendations are: Recommendation 10.1: Consideration should be given to extending the platform created to enforce payments and administer income contingent loans through the tax system; for instance, by extending income contingent loans for tertiary education outside universities and for sole trader entrepreneurs seeking to fund innovative projects. Recommendation 10.2: An advisory committee of web 2.0 practitioners should be established to propose and help steer governments as they experiment with web 2.0 technologies and ideas. Recommendation 10.3 An Advocate for Government Innovation should be established to promote innovation in the public sector. Recommendation 10.4: A rigorous policy of evaluating all Australian Government innovation programs ­ and other re

The Australian government has just released a report " Review of the National Innovation System Report - Venturous Australia" . Given the similarities on size and nature of our economies, innovation, higher education and R&D environments, this report should be examined by Canadians interested in our own national innovation system. The Australian minister for Innovation, Industry, Science and Research (just having a ministry so named is a Good Thing!), Kim Carr spoke about this report in a speech released yesterday and talks about - among other interesting things for those interested in national innovation and R&D strategy - Creative Commons and Open Access to research outputs: It is embodied in a series of recommendations aimed at unlocking public information and content, including the results of publicly funded research. The review panel recommends making this material available under a creative commons licence through: machine searchable repositories, especially

The latest Nature -- Vol 455(7209), 4 September 2008 -- is a special issue on " Big Data ". Articles (& editorial) include: Editorial (2008). Community cleverness required Nature, 455 (7209), 1-1 DOI: 10.1038/455001a David Goldston (2008). Big data: Data wrangling Nature, 455 (7209), 15-15 DOI: 10.1038/455015a Cory Doctorow (2008). Big data: Welcome to the petacentre Nature, 455 (7209), 16-21 DOI: 10.1038/455016a Mitch Waldrop (2008). Big data: Wikiomics Nature, 455 (7209), 22-25 DOI: 10.1038/455022a Clifford Lynch (2008). Big data: How do your data grow? Nature, 455 (7209), 28-29 DOI: 10.1038/455028a Sue Nelson (2008). Big data: The Harvard computers Nature, 455 (7209), 36-37 DOI: 10.1038/455036a Doug Howe, Maria Costanzo, Petra Fey, Takashi Gojobori, Linda Hannick, Winston Hide, David P. Hill, Renate Kania, Mary Schaeffer, Susan St Pierre, Simon Twigger, Owen White, Seung Yon Rhee (2008). Big data: The future of biocuration Nature, 455 (7209), 47-50 DOI: 10.103

This is a little off-topic, but I need to rant: I have several types of those inexpensive outdoor solar powered light thingies. You know, they come with a plastic spike to plant them in the ground or hang from the side of your house (Wikipedia calls them " Solar lamps "). Here, one of these: From Wikipedia: http://en.wikipedia.org/wiki/Image:Solarlight.JPG These are great things, but they turn on too early, when it is still too bright out, wasting energy. Right now, Sept 2ish, where I live ( Ottawa area, Canada), they turn on about 45+ minutes before the sun goes down. Yes, you can see them, but these things are so low intensity that they are not useful until around when the sun goes down. But it means they are burning 45-60 minutes of power being on but being useless. As they often do not have enough juice to stay lit all night, this makes a difference. Adding a way of altering the light level causing these little things turn on would increase their price slightly (which

In the September issue of PLOS Medicine , Piwowar et al. [1] examine the benefits and offer recommendations to encourage data sharing at academic health centers (AHC): Commit to sharing research data as openly as possible, given privacy constraints. Streamline IRB (Institutional Review Board), technology transfer, and information technology policies and procedures accordingly. Recognize data sharing contributions in hiring and promotion decisions, perhaps as a bonus to a publication's impact factor. Use concrete metrics when available. Educate trainees and current investigators on responsible data sharing and reuse practices through class work, mentorship, and professional development. Promote a framework for deciding upon appropriate data sharing mechanisms. Encourage data sharing practices as part of publication policies. Lobby for explicit and enforceable policies in journal and conference instructions, to both authors and peer reviewers. Encourage data sharing plans as part o

In the October 2008 special issue on inductive logic programming in Machine Learning , Dietterich et al [ 1 ] lay-out the following ten outstanding problems for the next ten years: Statistical predicate invention Generalizing across domains Learning many levels of structure Deep combination of learning and inference Learning to map between representations Learning in the large Structured prediction with intractable inference Reinforcement learning with structured time Expanding SRL (Statistical Relational Learning) to statistical relational AI Learning to debug programs [ 1 ] Thomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli (2008). Structured machine learning: the next ten years Machine Learning, 73 (1), 3-23 DOI: 10.1007/s10994-008-5079-1

One of the implications of research data archiving is that there will likely be large datasets on a variety of subjects. How third parties will analyse these data in a scalable fashion has not entirely been addressed. But the recent conference examines some of the issues for a class of data, images and signals : Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry (Third International Conference, MDA 2008 Leipzig, Germany, July 14, 2008) and includes: Burcu Yılmaz, Mehmet Göktürk, Natalie Shvets (2008). User Assisted Substructure Extraction in Molecular Data Mining. Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, 5108 , 12-26 DOI: 10.1007/978-3-540-70715-8_4 Franco Chiarugi, Sara Colantonio, Dimitra Emmanouilidou, Davide Moroni, Ovidio Salvetti (2008). Biomedical Signal and Image Processing for Decision Support in Heart Failure. Advances in Mass Data Analysis of Imag