MAL8

The Generic Mapping Tools (GMT; www.generic-mapping-tools.org) is a well-known set of software for the geosciences, in particular in the marine and solid earth disciplines. GMT is also a prerequisite for many other well-known software infrastructures, including USGS’s ShakeMap for near-real-time maps of ground motion and shaking intensity following significant earthquakes, MBARI/LDEO’s MB-System for multibeam processing and mapping of the seafloor, and Scripps Institution of Oceanography’s GMTSAR for radar interferometric analysis and imaging of crustal deformation. Today, GMT has tens of thousands of users all over the world and remains essential for many terrestrial and planetary data processing and map-making workflows. GMT began its life over 30 years ago when I was a graduate student, and it has enjoyed continuous US National Science Foundation funding since 1993. Leveraging this funding, GMT has succeeded in establishing itself as a collaborative Open Source community resource from the start. Many scientists globally, particularly European scientists, have been instrumental in designing, maintaining, and improving GMT since the early 2000s. As I and several of our core developers approach the end of our academic careers, the GMT team has been pondering how to preserve these collective investments and position GMT to remain an essential geoinformatics infrastructure well into the future. In response, we have made fundamental changes to how GMT works, enabling access to GMT modules from external interfaces such as MATLAB/Octave, Python, and Julia, simplifying user access to large global datasets, and extending our support for the Google Earth platform. However, the biggest impact delivered by the Fall 2019 release of GMT 6 is likely “modern mode”. Modern mode coexists with classic mode (the only previous mode) so that thousands of GMT 4 and 5 scripts will still run as expected. Furthermore, new users will start with modern mode and experience a much-simplified GMT scripting syntax. A new aspect of GMT made possible by modern mode is a greatly simplified animation production. It is clear to all scientists that animations make it easier to elucidate temporal or spatial changes, yet very few scientists create animations as they are traditionally the domain of experts. The GMT team aspires to make animations a task every scientist can do with ease. In this lecture, I will discuss the latest news on GMT, outline modern mode and the external environment access to our modules, highlight a few GMT animations, and present other aspects of our succession planning for strengthening the GMT community.

How to cite: Wessel, P.: The Generic Mapping Tools and Community-Maintained Open Source Software, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-612, https://doi.org/10.5194/egusphere-egu21-612, 2021.

Open data is not a new concept. Over sixty years ago in 1959, knowledge sharing was at the heart of the Antarctic Treaty which included in article III 1c the statement: “scientific observations and results from Antarctica shall be exchanged and made freely available”. ​At a similar time, the World Data Centre (WDC) system was created to manage and distribute the data collected from the International Geophysical Year (1957-1958) led by the International Council of Science (ICSU) building the foundations of today’s research data management practices.

What about now? The WDC system still exists through the World Data System (WDS). Open data has been endorsed by a majority of funders and stakeholders. Technology has dramatically evolved. And the profession of data manager/curator has emerged. Utilising their professional expertise means that their role is far wider than the long-term curation and publication of data sets.

Data managers are involved in all stages of the data life cycle: from data management planning, data accessioning to data publication and re-use. They implement open data policies; help write data management plans and provide advice on how to manage data during, and beyond the life of, a science project. In liaison with software developers as well as scientists, they are developing new strategies to publish data either via data catalogues, via more sophisticated map-based viewer services or in machine-readable form via APIs. Often, they bring the expertise of the field they are working in to better assist scientists satisfy Findable, Accessible, Interoperable and Re-usable (FAIR) principles. Recent years have seen the development of a large community of experts that are essential to share, discuss and set new standards and procedures. The data are published to be re-used, and data managers are key to promoting high-quality datasets and participation in large data compilations.

To date, there is no magical formula for FAIR data. The Research Data Alliance is a great platform allowing data managers and researchers to work together, develop and adopt infrastructure that promotes data-sharing and data-driven research. However, the challenge to properly describe each data set remains. Today, scientists are expecting more and more from their data publication or data requests: they want interactive maps, they want more complex data systems, they want to query data, combine data from different sources and publish them rapidly.  By developing new procedures and standards, and looking at new technologies, data managers help set the foundations to data science.

How to cite: Fremand, A.: Supporting open data: the key role of data managers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4055, https://doi.org/10.5194/egusphere-egu21-4055, 2021.