There are several places at the LMU where you can find help to implement open research practices in your own work:
Research Funding Unit: what are grant agencies' Open Science requierements
The Research Funding Unit is here to help researchers comply to requierements of funding agencies to increase your chances of getting funded.
For advice on how to comply to Open Science requierements, contact:
- Dr. Florian Schreck at firstname.lastname@example.org if you are considering applying for a National Grant Agency (e.g. DFG),
- Dr. Veit Schwab at email@example.com if you are considering applying for an International Funding Agency (e.g. Horizon Europe).
Open Science Center: from concepts to implementation
- how to join open science meetups to meet like-minded researchers and exchange implementation tips,
- where to get formal or informal training provided by expert researchers,
- which open research practices is relevant for your type of research
- design; e.g. preregistration, registered reports, simulation of data, power analyses, data sharing planning
- analysis; e.g. reproducible code, reproducible computational environment, version control, literate programming, free and open source software
- reporting; reporting guidelines, transparent writing (e.g. preregistration and stage 1 registered report deviations, no HARKING (Hypothesizing After the Resuts are Known))
- preservation: data anonymity, privacy and security, metadata, copyrights, reuse agreement, licences, DOI
- dissemination; FAIR data sharing, preprint, postprint, open access publishing.
- replication, meta-analyses, and meta-research work.
- research assessment reforms, team science, adversarial collaboration, and other aspects of academic research culture.
StaBLab: Statistical consulting unit
The StaBLab team provide free statistical consultations for LMU students and researchers to support them with their thesis and research projects with, e.g.:
- Experimental design and sampling planning
- Statistical modelling
- Big Data Analyses & Machine Learning
MLCU: Machine Learning Consulting Unit
- help with selection of appropriate methods to answer specific research questions
- support with implementation and interpretation of machine and deep learning methods
- support in setup and implementation of reproducible benchmark experiments (including hyperparameter optimization and benchmark evaluation)
- different ways of collaboration (e.g. joint thesis or PhD supervision)
University Library LMU - Research Data Management HelpDesk: General RDM Support and Infrastructures
The RDM HelpDesk team at the University Library LMU provides infrastructure and gives advice on
- how to start your research data management
- how to write RDM plans (e.g. with the tool RDMO)
- how to make your data FAIR (findable, accessible, interoperable, reusable), and
- how to use data repositories, including the infrastructure "Open Data LMU".
University Library LMU - Open Access team: Open Access Publishing Funds and Open Infrastructure
The University Library provides
- Infrastructure to preserve and share articles or books following the Green or Gold Open Access route (e.g. preprint, postprints, articles, monographs): Open Access LMU
- Infrastructure for your own Open Access journal: Open Journals LMU
- Infrastructure to publish your university thesis or monograph in both print and digital form as Open Access publication: Open Publishing LMU
- Funds to cover article or book processing charges: Open Access publishing Fund
- Framework contracts or memberships with some publishers, through which Open Access publications can be published free of charge or at a reduced price: Funding of article processing charges
IT-Gruppe Geisteswissenschaften (ITG) - LMU Center for Digital Humanities
The ITG provides advice and assistance with
- planning and conducting projects with substantial shares of digital methods in the humanities
- research data management
The ITG is responsible for accompanying digital projects in the humanities, computer science, statistics and computational linguistics as well as the emerging data sciences.