Fostering Data and Information Sharing for The Dark Matter Community

Open Data, Open Science!

Open science has become a pillar in the research world and it's fuelling exchange of knowledge, data and ideas. The extraordinary impact of open science accelerates scientific research and the creation of new knowledge. We believe that open data is deeply rooted in the scope and spirit of fundamental research and we support this culture, offering a place where data from experiments and phenomenology can meet.

Dark Matter

Dark matter searches are an extraordinary endeavor of the human kind to shed light on one of the biggest mysteries of the cosmos and the physics that governs it. The understanding of the composition of our Universe expands through a variety of experimental approaches and a rich zoo of models and ideas. The discovery of dark matter and the investigation of its nature must follow complementary paths, for no single evidence would uniquely identify the nature of dark matter making up our Universe.

Bringing Experiments and Theories Together

With the ORIGINS Dark Matter Data Center we want to fully leverage the potential of open science to bring together observations from different experiments, the implications of different models and all the associated software. At the DMDC we aim at increasing accessibility to scientific process and knowledge, open data and open source software: key ingredients for the nourishing of open science (From "Open Data to Open Science" Earth and Space Science doi:10.1029/2020EA001562), by offering a repository for experimental data, models and code. The Dark Matter Data Center supports data comparison, combination and interpretation using clear and reproducible methodologies, easing the usability of this data, enabling one to make the most out of it. Our sights are set on sharing knowledge in all its relevant forms: data, methodologies and software with the ultimate goal of offering a consistent and unified view of the field in all its facets.

 

If you want to make your code, models or data public, or need support for your own project, do not hesitate to get in touch with us!

Explore Data

Dark matter experiments are based on widely varying technologies and the data from these experiments are also very different in the way they need to be understood and analysed. The DMDC allows you to fully understand, visualise and test the usage of all the resources from all the listed Collaborations before you download them. Here you can,

  • Browse datasets from several experiments, the Collaboration pages list all the datasets they have made available.
  • Each resource in a dataset has associated usage descriptions. You can download individual resources as well.
  • Visualise the resources online through interactive plots.
  • Test the usage of these resources in JupyTer Notebooks that run online; no downloads, no installations. These vetted code snippets are provided directly by the Collaborations.

Publish Data

Publish Dark Matter data directly on the Dark Matter Data Centre!

  • Publish and manage your datasets from our Git interface provided by the Max Planck Computation & Data Facility.
  • Include JupyTer Notebooks in your Projects that can be run online through the MPCDF BinderHub. Your analysis workflows stay safe here in persistent virtual environments.
  • Each dataset is associated with full metadata that includes all public information, including the resource descriptions and URLs.
  • You have full control over your datasets through your own assigned maintainers (upto two for each Collaboration).
  • Publish your data visualizations as interactive plots by putting their HTMLs on your Projects.
  • We can help you prepare your datasets, visualizations and JuPyter Notebooks if you need it!

Publish Your Codes

Have you just published a model of physics concerning the presence of Dark Matter? Publish the software implementation of your model!

Have you designed a new simulator for DM-nucleus/electron events? Publish your code here!

Have you designed any new software package that is useful in DM research? Publish your code here!

  • Covenient storage for long-term utility and reproducibility.
  • It will help those coming after you to learn and build upon your work.
  • It will add to the repository of hypotheses that can be analysed in tandem and compared for a unified view of the work that has already been done.
  • Contact us directly for submissions!