Here you can find first steps into Open Science…

General information

Here you can find information about general Open Science practices...

The term ‘Open Science’ describes various practices that have the goal to make scientific research more transparent and accessible. This should make research results more reliable, facilitate collaborations, and improve efficiency and quality of scientific research. Open Science practices include, for example, making all materials, data and code available for the public, publishing research results in open access journals and pre-registering studies.  

Further information:

Open data refers to making research data publicly available. In this way, the data can be reviewed to identify possible errors or confirm reported results, and it can further be reused beyond its original purpose, e.g. to explore related hypotheses, to conduct meta-analyses or to be subject to a historical analysis. There are several repositories where data can be made available to anyone. However, legal and ethical frameworks have to be considered when sharing data. In particular, it should be noted that data sets must be anonymized in order not to be subject to data protection laws. This means that the data do not or no longer allow an individual to be identified or become identifiable – either by specific information referencing the person or by any information that could be used by someone with knowledge of the individual to re-identify him or her. Please note that certain kinds of data (e.g., genetic or certain biometrical data) cannot be anonymized with currently available methods. Furthermore, copyright issues may also need to be considered.


Examples of repositories for making data publicly available:

A list of generalist repositories and registries of all repositories can be found here:

Further information: 

What is open and FAIR data?

What is research data management? 

Introduction to repositories 

Legal questions in Open Science/ Research ethics and data protection

Anonymisation of data


Use open data in teaching

Steps to share your data

Publications are defined ‘open access' when they are downloadable free of cost and without any legal or technical barriers. The advantage is that a more equitable system of access to knowledge is provided. 

Two routes to open access can be distinguished: The gold route to open access means that the publication is immediately free to access via the journal’s website. The journals, in this case, can either be fully open access journals (where all content is published open access) or hybrid journals (subscription-based journals with the option to publish open access). Gold open access typically requires an article processing charge. The green route to open access (also known as self-archiving) means that researchers place the preprint or post-print version of their manuscript into a repository. In this case, the open access policy of the journal that publishes the article must be considered. 


Further information 

List of Open Access journals

Sharing preprints

Deceptive publishing

Preregistration means that the study, hypotheses, and/or analysis plans are specified prior to implementation and execution. This is to prevent hypotheses from being adjusted to fit the data after the fact, to more clearly distinguish data-contingent analysis (exploratory) from confirmatory hypothesis testing, and to increase transparency and rigor of research which may help to strengthen confidence in results.

There are a variety of sites where you can create a timestamped document in which you specify your study hypotheses and data analysis plans prior to your experiment/data analysis. For example:

Further information: 

Registered reports are a format of publication in which authors submit their manuscript to a journal prior to study implementation. In this way, methods and planned analyses are peer-reviewed before data collection and analysis. If the manuscript is accepted, the journal commits to publishing the study regardless of the results if the authors follow through with the registered methodology. After the study is completed and the data analyzed, a second peer review will take place to verify that the previously described protocol has been followed. Registered reports thus fulfill the same function as preregistrations, but additionally decouple the publication decision from the results.  As a consequence, this format reduces the rate of result-contingent publications and can help to reduce bias in the literature.

Further information:

A list of journals that offer the format can be found here (see Participating Journals):

Open Science not only refers to making data or code public, preregistering hypotheses or publishing Open Access. Open Science, at least in our understanding, also aims for policy changes on all levels of the academic system including employment status of scientists, questions of representation in committees and boards or the current incentive system.    


Employment status of PhDs, postdocs etc.:


Incentive system: 

Publish or perish: how our literature serves the anti-science agenda


Callaway, Ewen. 2016. “Beat It, Impact Factor! Publishing Elite Turns against Controversial Metric.” Nature 535 (7611): 210–11.


Editorial. 2006. “The Impact Factor Game. It Is Time to Find a Better Way to Assess the Scientific Literature.” PLoS Medicine 3 (6): e291.


Lariviere, Vincent, and Cassidy R. Sugimoto. 2018. “The Journal Impact Factor: A Brief History, Critique, and Discussion of Adverse Effects.” arXiv [cs.DL]. arXiv.


Paulus, Frieder M., Nicole Cruz, and Sören Krach. 2018. “The Impact Factor Fallacy.” Frontiers in Psychology 9 (August).


Brembs, Björn, Katherine Button, and Marcus Munafò. 2013. “Deep Impact: Unintended Consequences of Journal Rank.” Frontiers in Human Neuroscience 7: 291.


Heesen, R., & Journal of Philosophy Inc. (2018). Why the reward structure of science makes reproducibility problems inevitable. The Journal of Philosophy, 115(12), 661–674.

List of publications on the critique of the impact factor:


Representation/ Diversifying science


“Joint Commitment for Action on Inclusion and Diversity in Publishing”


Altman, Micah, and Philip N. Cohen. 2021. “Openness and Diversity in Journal Editorial Boards.”


Eaton, Asia A., Jessica F. Saunders, Ryan K. Jacobson, and Keon West. 2020. “How Gender and Race Stereotypes Impact the Advancement of Scholars in STEM: Professors’ Biased Evaluations of Physics and Biology Post-Doctoral Candidates.” Sex Roles 82 (3): 127–41.


Ginther, Donna K., Walter T. Schaffer, Joshua Schnell, Beth Masimore, Faye Liu, Laurel L. Haak, and Raynard Kington. 2011. “Race, Ethnicity, and NIH Research Awards.” Science 333 (6045): 1015–19.


Ginther, Donna K., Jodi Basner, Unni Jensen, Joshua Schnell, Raynard Kington, and Walter T. Schaffer. 2018. “Publications as Predictors of Racial and Ethnic Differences in NIH Research Awards.” PloS One 13 (11): e0205929.


Eisen, Michael B. 2020. “Racism in Science: We Need to Act Now.” eLife 9 (June).

Lübeck specific information

Here you can find information about how to approach Open Science at Lübeck University...

The University of Lübeck has recognized the important role of Open Science for the future of scientific research and aims to promote open science practices:

"Ein offener Zugang zu wissenschaftlichen Veröffentlichungen (Open Access), Forschungsdaten (Open Data) und wissenschaftlicher Software (Open Sources) ist essenziell als Bestandteil der Sicherung guter wissenschaftlicher Praxis und fördert eine partizipative Forschung unter Einbeziehung verschiedenster Akteur*innen. Die UzL wird die Grundprinzipien von offener Wissenschaft wie Transparenz, Reproduzierbarkeit, Wiederverwendbarkeit und offene Kommunikation als wichtiges Ziel verankern und intensivieren"  (Struktur-und Entwicklungsplan der Universität zu Lübeck III, 07/2022- 06/2027, p. 15-16)

Open Data is increasingly demanded by research funders and journals, but in human research there is often a tension between data sharing and data protection. Furthermore, it might be unclear who owns the copyright on your data. For ethical and legal sharing of data the following information should be considered:


  • Anonymisation

The data you share must be anonymized in order not to be subject to data protection laws. Sec 13 (2) Schleswig-Holstein Law for the Protection of Personal Data (LDSG SH) provides the following:


“…sind zu wissenschaftlichen oder historischen Forschungszwecken oder zu statistischen Zwecken verarbeitete personenbezogene Daten so zu verändern, dass die Einzelangaben über persönliche oder sachliche Verhältnisse nicht mehr oder nur mit einem unverhältnismäßig großen Aufwand einer bestimmten oder bestimmbaren natürlichen Person zugeordnet werden können (Anonymisierung), sobald dies nach dem Forschungs- oder Statistikzweck möglich ist, es sei denn, berechtigte Interessen der betroffenen Person stehen dem entgegen.”


It must be clear that anonymisation not only means removing directly identifying information (such as the person`s name, address, or birth date) but also to prevent identifiability by any piece of information that could be used (in combination with other information) by someone who has knowledge about an individual (think also of people such as ex-partners, co-worker, or fellow patients who might know about study participation). For example, in a small study sample, only gender and age might be sufficient to identify a person. Also, the exact date of an investigation, in combination with other publicly available information (e.g., posts on social media that are not directly related to study participation but reveal the study location), may be sufficient to identify an individual. Therefore, it is very important to carefully consider which data need to be removed and which data require additional measures before they can be published. Such a measure can be, for example, generalizing – changing data into a range of values (information on anonymization techniques by the European Commission can be found under General information: Open Data – what, why, and how?). In some cases, it may not be possible to publish raw data at all, however you still might have the option to provide aggregated data.

If you have questions, you can contact Datenschutzbeauftragter der Universität zu Lübeck or the Open Science Initiative Lübeck.


  • Informed consent

When you plan to share data, you should obtain informed consent from your participants. We recommend to add the following paragraph to your information on data protection in your study information, as far as the data in question can be subject to anonymisation (approved by Datenschutzbeauftragter der Universität zu Lübeck):


„Veröffentlichung der anonymisierten Daten

"Ihre anonymisierten Daten werden in einer Datenbank im Internet zur Nachnutzung öffentlich zugänglich gemacht. Eine Identifizierung Ihrer Person ist dabei weitestgehend ausgeschlossen. Zweck, Art und Umfang potentieller Nachnutzungen können zum jetzigen Zeitpunkt noch nicht abgesehen werden. Eine Löschung Ihrer Daten aus dem anonymisierten Datensatz ist nicht mehr möglich.“



3) Copyright

If you plan to share data, you should clarify who owns the copyrights to the data sets and make sure you are allowed to publish the data. This depends on many factors, information can be found under General information: Open Data – what, why, and how?.



Here you can find a visualization of how Open Access publications can be realized at the UzL: OA_University_of_Lübeck

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