A new inductee in the Madagascar Hall of Fame is Jim Jennings.
You can read Jim’s story here.
The first ever worldwide Madagascar conference will take place on June 21-27, 2021. The participation is free of charge.
The conference program will be announced later. Meanwhile, please indicate the level of your interest in participation by filling a form on the website.
American Innovation and Competitiveness Act was adopted unanimously by the U.S. Congress and signed into law by president Obama in January 2017.
The law contains a section called Research Reproducibility and Replication, which asked the Director of the National Science Foundation in agreement with the National Research Council to prepare a report on issues related to research reproducibility and “to make recommendations for improving rigor and transparency in scientific research”.
To fulfill this requirement, a consensus report of the National Academies of Sciences, Engineering, and Medicine was published in 2019. The report is summarized in the special issue of Harvard Data Science Review in December 2020.
Among the recommendations:
All researchers should include a clear, specific, and complete description of how the reported results were reached. Reports should include details appropriate for the type of research, including:
Funding agencies and organizations should consider investing in research and development of open-source, usable tools and infrastructure that support reproducibility for a broad range of studies across different domains in a seamless fashion. Concurrently, investments would be helpful in outreach to inform and train researchers on best practices and how to use these tools.
Journals should consider ways to ensure computational reproducibility for publications that make claims based on computations, to the extent ethically and legally possible.
The major version of Madagascar, stable version 3.0, has been released. The main change is the added support for Python-3. Both Python-2 and Python-3 are now supported. The new version also features 14 new reproducible papers, as well as other enhancements.
According to the SourceForge statistics, the previous 2.0 stable distribution has been downloaded about 6,000 times. The top country (with 27% of all downloads) was China, followed by the USA, Brazil, Canada, and India.
In September 2019, the total cumulative number of downloads for the stable version of Madagascar has reached 50 thousand. The current development version continues to be available through Github.
Working Workshops as opposed to “talking workshops” are meetings where the participants collaborate in small groups to develop new software code or to conduct computational experiments addressing a particular problem.
The 2018 Working Workshop took place in Houston on August 8-11. It was hosted by the University of Houston and organized by Karl Schleicher. The topic of the workshop was Python and Julia programming languages, as well as their interfaces to Madagascar.
The workshop attracted 16 participants (students, academic staff, and industry professionals) from 12 different organizations. Software projects included such topics as machine learning, 3D plotting, parallel processing, wave equation modeling, and well log analysis.
A new paper is added to the collection of reproducible documents: Matching and merging high-resolution and legacy seismic images
When multiple seismic surveys are acquired over the same area using different technologies that produce data with different frequency content, it may be beneficial to combine these data to produce a broader bandwidth volume. In this paper, we propose a workflow for matching and blending seismic images obtained from shallow high-resolution seismic surveys and conventional surveys conducted over the same area. The workflow consists of three distinct steps: (a) balancing the amplitudes and frequency content of the two images by non-stationary smoothing of the high-resolution image; (b) estimating and removing variable time shifts between the two images; and (c) blending the two images together by least-squares inversion. The proposed workflow is applied successfully to images from the Gulf of Mexico.