![]() Who's attending page and what people hope to learn by attending the workshop. If any of the stated benefits is of interest to you, then you should attend also, even if you don't fall into one of the categories above.įor me information please read these Collaboration Workshop attendee quotes. Publishers can gain an insight about the direction of reproducible science, which is a popular topic at the Collaborations Workshop, and can better understand grassroots level thinking about future trends in publication. Investigators and managers gain a more up to date understanding of themes in collaborative research and how best to bring together researchers and developers for better project outcomes.įunders gain an understanding of the thriving and moving target of interdisciplinary research and why and how it should be best funded. Similarity and differences in the computational needs of different disciplines. Participation by software developers allows them to better understand real user needs and appreciate the The workshop enables researchers to connect with software developers who have the skills to implement their research ideas and to understand the approaches taken by different researchers and see how this might be applicable to their own work. We'll announce all Collaborations Workshop related news on Twitter with the hashtag #collabw13. The 2013 workshop will be held at Merton College at the University of Oxford on 21-22 March 2013. The information shown on the original Collaborations Workshop 2013 page is shown below. If you're looking for archived information, visit the archive page. ![]() The agenda is also available.Īs Collaborations Workshop pages are superseded, they are added to the archive page. Although the delegates list is not publicly available, the list of attending organisations is available.The introductory talks from Neil Chue Hong ( Introduction to the SSI), David De Roure ( Digital Social Research) and Steve Brewer ( The role of the ITaaU Network+ in bringing together researchers and others to explore and promote the role of IT utilities in the digital economy), and the wrap up from Neil Chue Hong can be downloaded.The screencasts of the selected talks are also available there. The list of lightning talks presenters and titles can be found on the lightning talks topics page.The delegates came up with 17 recommendations for improvements and changes and made 17 pledges.The best Collaborative Idea of CW13 turned out to be "Low-risk high-impact micro-collaboration". The collaborative ideas sessions led to 19 ideas for collaborations."Five important things" is the name given to the five most important lessons learned during each break out discussion.Anyone can access the group and read the notes. All discussions and detailed notes from the break outs are logged in the Google Group that was used to run the conference (as described on the email everything page).Outcomes and downloadsĪpart from the exchange of information and the new contacts made by the delegates, the following list covers the main outcomes from the Collaborations Workshop 2013. Please see this news item for more details. It was held at Merton College at the University of Oxford on 21-22 March 2013. The Collaborations Workshop 2013 is now successfully completed. The Software Sustainability Institute's annual Collaborations Workshop brings together researchers, software developers, managers, funders and more to explore important ideas in software and research and to plant the seed of interdisciplinary collaborations. A news item on outcomes at CW13 and an Fellow's report on CW13 is available debug ( pk ) print ( "Secret parameters." ) group. ![]() init ( ZR, 1 )]])] Bstar = MatrixTransGroups ( Bstar ) # checks Bt * Bstar = identity matrix # for i in self.MatrixMulGroups(Bt, Bstar): # print(""%(i,i)) #generate R R =, ] #generate A1 and A2 A1 =, ] A2 =, ] k = #k is a 2 dimentional vector BA1 = MatrixMulGroups ( B, A1 ) BA2 = MatrixMulGroups ( B, A2 ) BsR = MatrixMulGroups ( Bstar, R ) BsA1R = MatrixMulGroups ( MatrixMulGroups ( Bstar, MatrixTransGroups ( A1 )), R ) BsA2R = MatrixMulGroups ( MatrixMulGroups ( Bstar, MatrixTransGroups ( A2 )), R ) b0 =, B ] b1 =, BA1 ] b2 =, BA2 ] b0s =, BsR ] b1s =, BsA1R ] b2s =, BsA2R ] #generate the mpk g1b0 =, g1 ** b0 ] g1b1 =, g1 ** b1 ] g1b2 =, g1 ** b2 ] egg = ( pair ( g2, g1 )) ** ( k * b0 + k * b0 ) pk = if ( debug ): print ( "Public parameters." ) group. init ( ZR, 0 )]]), GaussEliminationinGroups (, Bt, group. random ( G2 ) #generator in G2 #generate B and B* B = ,] Bt = MatrixTransGroups ( B ) Bstar =, Bt, group. random ( G1 ) #generator in G1 g1 = group.
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