[{"id":103,"title":"Develop a human-readable formal language for complex scientific models","sha":"27deb8bb6d86c83d29f53320f02a22a5","user_id":250,"state":"published","body":"Much modern research is based on complex models for complex systems. Examples are biological macromolecules, climate models, or systems biology. These models are too complex for publishing in journal articles. They currently exist only in the heads of a few experts and embedded in simulation software, inaccessible for inspection by peers. Most users of simulation software have no precise knowledge of the models they are applying. See [here](http://dx.doi.org/10.12688/f1000research.3978.2) for an in-depth discussion.\r\n\r\nSuch models should be encoded in [formal languages](http://en.wikipedia.org/wiki/Formal_language) designed for this purpose. In contrast to programming languages, these languages are designed for simplicity and readability by humans. Formalized complex models can then be used for testing simulation software, and read as input by future simulation software. They can also be worked on by software tools similar to today's computer algebra systems, and published as datasets.\r\n\r\nThe idea is similar to the use of [specification languages](http://en.wikipedia.org/wiki/Specification_language) for software. A specification for scientific software would consist of several models plus a task to be performed based on these models. A formal language for scientific models would be a hybrid of a software specification language and a notation like [OpenMath](http://www.openmath.org/).\r\n","created_at":"2015-02-27T08:56:20.512Z","updated_at":"2023-04-22T15:39:45.301Z","zenodo_id":23586,"doi":"http://dx.doi.org/10.5281/zenodo.15700","subject":null,"tags":["computational science","complex systems","formal methods"],"vote_count":26,"view_count":1,"score":26.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":350,"title":"Make computer-aided research more verifiable","sha":"a517110ddc80ad0b7fe03a477fd82375","user_id":null,"state":"published","body":"A central problem with modern computer-aided research is that research based on long computations becomes difficult to verify. It is thus unclear how and why such should be trusted. The most widely discussed aspect of this problem is the (non-)reproducibility of computational work, but the issue goes deeper: even 100% reproducible work can be wrong because of a software bug, an implicit assumption in the code that is not documented, etc.\r\n\r\nOne measure to improve the situation is to require authors who use computers in their research to state in a short section of each paper (1) what they have done to validate their methods and their software and (2) how readers can attempt an independent verification of the work. Reviewers would then check if those statements match or exceed the current state of the art. The goal is to bring the discussion about the problem out in the open, in a way that nobody can simply ignore it. The measure acts as both carrot and stick: good verifiability approaches can be showcased, and insufficient ones can be recognized more easily.\r\n","created_at":"2016-11-25T13:22:30.066Z","updated_at":"2021-11-15T20:01:02.951Z","zenodo_id":171845,"doi":"https://doi.org/10.5281/zenodo.171845","subject":null,"tags":["computer-aided research","verifiability","reproducibility"],"vote_count":2,"view_count":1,"score":2.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null}]