{"action":"created","issue":{"url":"https://api.github.com/repos/pangeo-data/pangeo/issues/514","repository_url":"https://api.github.com/repos/pangeo-data/pangeo","labels_url":"https://api.github.com/repos/pangeo-data/pangeo/issues/514/labels{/name}","comments_url":"https://api.github.com/repos/pangeo-data/pangeo/issues/514/comments","events_url":"https://api.github.com/repos/pangeo-data/pangeo/issues/514/events","html_url":"https://github.com/pangeo-data/pangeo/issues/514","id":391150126,"node_id":"MDU6SXNzdWUzOTExNTAxMjY=","number":514,"title":"BiDS 2019 : Paper enhancement by the 15th of january","user":{"login":"guillaumeeb","id":17138587,"node_id":"MDQ6VXNlcjE3MTM4NTg3","avatar_url":"https://avatars0.githubusercontent.com/u/17138587?v=4","gravatar_id":"","url":"https://api.github.com/users/guillaumeeb","html_url":"https://github.com/guillaumeeb","followers_url":"https://api.github.com/users/guillaumeeb/followers","following_url":"https://api.github.com/users/guillaumeeb/following{/other_user}","gists_url":"https://api.github.com/users/guillaumeeb/gists{/gist_id}","starred_url":"https://api.github.com/users/guillaumeeb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/guillaumeeb/subscriptions","organizations_url":"https://api.github.com/users/guillaumeeb/orgs","repos_url":"https://api.github.com/users/guillaumeeb/repos","events_url":"https://api.github.com/users/guillaumeeb/events{/privacy}","received_events_url":"https://api.github.com/users/guillaumeeb/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":4,"created_at":"2018-12-14T15:15:33Z","updated_at":"2018-12-17T15:56:10Z","closed_at":null,"author_association":"MEMBER","body":"The Pangeo talk for [BiDS](https://www.bigdatafromspace2019.org) (see #376 ) has been accepted! However, this was not a formality as I thought it would be, we've encountered a tough second reviewer (see below). I will try to work on an update, schedule is tight, any suggestions/improvement would be appreciated.\r\n\r\nFor a reminder, paper is available here: https://github.com/guillaumeeb/bids2019.\r\n\r\n\r\n> ----------------------- REVIEW 1 ---------------------\r\n> PAPER: 17\r\n> TITLE: The Pangeo Big Data Ecosystem and its use at CNES\r\n> AUTHORS: Guillaume Eynard-Bontemps, Ryan Abernathey, Joseph Hamman and Aurélien Ponte\r\n> \r\n> Suitability for Big Data from Space conference: 4 (good)\r\n> Originality: 4 (good)\r\n> Technical quality: 3 (fair)\r\n> Readability: 4 (good)\r\n> Bibliography: 3 (fair)\r\n> Overall evaluation: 2 (accept)\r\n> \r\n> ----------- Overall evaluation -----------\r\n> The authors present an open source toolset for Big Data processing using Python. It is based on Juypter fo interactive computing and analysis via the web browser, Dask for parallel computing and Xarray for the data model. The abstract is clear and the subject is relevant for this BiDS conference. As the proposed toolset seems somehow overlapping with the existing Orfeo Toolbox (OTB, also developed by CNES), it is surprising that no reference to OTB is given. The authors should comment on the existing overlap, difference, pro's and con's of each of the packages and, in particular, on the reason why this new initiative was started.\r\n> \r\n> Some more technical details on the implementation would be welcome. The figures 1,3, and 4 are hardly readable and should be improved.\r\n> \r\n> \r\n> ----------------------- REVIEW 2 ---------------------\r\n> PAPER: 17\r\n> TITLE: The Pangeo Big Data Ecosystem and its use at CNES\r\n> AUTHORS: Guillaume Eynard-Bontemps, Ryan Abernathey, Joseph Hamman and Aurélien Ponte\r\n> \r\n> Suitability for Big Data from Space conference: 2 (poor)\r\n> Originality: 2 (poor)\r\n> Technical quality: 2 (poor)\r\n> Readability: 4 (good)\r\n> Bibliography: 3 (fair)\r\n> Overall evaluation: -1 (weak reject)\r\n> \r\n> ----------- Overall evaluation -----------\r\n> The abstract introduces Pangeo, a tool aiming at giving scalable support to scientific data analysis, which boils down to support for n-D arrays. \r\n> \r\n> Interestingly, interoperability is not considered by the authors, and Pangeo does not seem to support the relevant open standards, such as OGC WCS. This certainly is a drawback in practice. \r\n> \r\n> The technology stack lists a shopping basket of tools plugged together (and that has been done elsewhere), but does not explain the specific innovation - for example, how can the generic Dask library help with the specific data structures of xarray? Can it only do the trivial, \"embarrassingly\" parallel operations or can it also efficiently parallelize data fusion, such as SciDB and rasdaman and others? How? Despite the title of Section 2.3 this does not become clear.\r\n> \r\n> Talking of that, relating to the state of the art is missing completely.\r\n> \r\n> There is a gap between the python interface and the \"one click\" request described - how is that accomplished? What about security when python code from the Internet is executed blindly on a server? How powerful is the single-click interface? Etc.\r\n> \r\n> Benchmark results, best comparing to other systems, would have been helpful.\r\n> \r\n> Finally, a neutral comment: There is the well-known portal Pangea, it seems not very advantageous to choose a name that is so close phonetically and in spelling."},"comment":{"url":"https://api.github.com/repos/pangeo-data/pangeo/issues/comments/447895059","html_url":"https://github.com/pangeo-data/pangeo/issues/514#issuecomment-447895059","issue_url":"https://api.github.com/repos/pangeo-data/pangeo/issues/514","id":447895059,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0Nzg5NTA1OQ==","user":{"login":"guillaumeeb","id":17138587,"node_id":"MDQ6VXNlcjE3MTM4NTg3","avatar_url":"https://avatars0.githubusercontent.com/u/17138587?v=4","gravatar_id":"","url":"https://api.github.com/users/guillaumeeb","html_url":"https://github.com/guillaumeeb","followers_url":"https://api.github.com/users/guillaumeeb/followers","following_url":"https://api.github.com/users/guillaumeeb/following{/other_user}","gists_url":"https://api.github.com/users/guillaumeeb/gists{/gist_id}","starred_url":"https://api.github.com/users/guillaumeeb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/guillaumeeb/subscriptions","organizations_url":"https://api.github.com/users/guillaumeeb/orgs","repos_url":"https://api.github.com/users/guillaumeeb/repos","events_url":"https://api.github.com/users/guillaumeeb/events{/privacy}","received_events_url":"https://api.github.com/users/guillaumeeb/received_events","type":"User","site_admin":false},"created_at":"2018-12-17T15:56:10Z","updated_at":"2018-12-17T15:56:10Z","author_association":"MEMBER","body":"Thanks everyone for the feedback. To be clear, R1 comment on OTB, and a good part of R2 review seems not really relevant to me. \r\n\r\nBut @willirath is probably right, this is just another world point of view, and we should try to make ourselves explicit about what we propose here. I personnaly have great trouble understanding the OGC world of often abstract standards, especially when talking about data analysis tooling. The most helpful standard here to me would be for the file format (Zarr for example). All the OGC standard seems defined from a consumer --> services provider perspective, which is kind of what @willirath  underlines.\r\n\r\n@fmaussion I'm not sure of what R2 refers to: the Jupyter + Dask + Xarray Pangeo core packages? I'm not sure what has been done elsewhere, and where..."}}
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