Glossary
Would you like to explore a comprehensive glossary of open scholarship terms? Check out the 
FORRT Glossary, a community-sourced glossary currently available in English, German, and Arabic!
Week 2: Transparency: As open as possible
Accessible: Research data is accessible if it can be accessed by anyone in the world, either openly or through an authentication or authorisation process. This requires metadata describing it in a standardised format.
Data: The information or facts collected, observed, or generated during the course of a study or investigation.
Data dictionary: A data dictionary is a collection of names, definitions, and attributes about data elements being used in shared data.
Findable: Research data is more findable by interested parties if it is stored in a well-organised repository with detailed metadata and persistent identifiers.
Interoperable: Datasets are interoperable if they can be used together to generate new studies. The metadata uses standard vocabularies, which are consistent across lots of different datasets.
Open data and materials: Data and materials from an open study are freely available to be used, reused, and redistributed by anyone.
Materials: Anything used in a study, eg: questionnaires, consent forms, protocols outlining what was done, the code used to run any statistical analyses, etc.
Metadata: Information that accompanies a piece of research, organising the materials, data and publications.
Reproducibility: A study is reproducible if, when you run the same analyses on the same data, you get the same results.
Open access repository: An open access repository is a digital platform that holds research output and provides free, immediate and permanent access to research data and materials.
Qualitative: A qualitative method is used to identify, analyse and report patterns (themes) in non-numerical data.
Quantitative: Quantitative methods deal with numbers, aiming to quantify phenomena and establish patterns or relationships.
Reusable: Research data is reusable if it can be used, modified or analysed, potentially by other researchers, to generate new knowledge. It needs to include clear information to facilitate re-use.
Secondary data analysis: A type of study where you use existing data to answer new questions.
Week 3: Integrity: Challenging Questionable Research Practices
Big team science: A research project in which researchers from around the world conduct the same study and pool their results.
Conceptual replications: A type of replication study which aims to vary some aspect of the original study, in order to better understand the underlying phenomenon.
Constraints on generality: A statement identifying populations sampled in the study and potential limits to the samples and methods, enabling others to assess the extent to which results can be generalised.
Direct replications: A type of replication study which aims to stay as close to the original study as possible.
False positive: An error that occurs when a researcher believes that there is a genuine effect or difference when there is not (e.g. a person has a positive Covid test although they do not have Covid).
False negative: An error that occurs when a researcher believes that there is no effect or difference, when actually there is (e.g. a person has a negative Covid test although they do have Covid).
Generalisability: The extent to which the findings of a study can be generalised to other situations, beyond the specific participants and conditions of the study.
HARK-ing: Researchers are HARK-ing if they write papers as if they had a hypothesis they wanted to test in their study, whereas in reality, they made up the hypothesis after seeing the results.
P-hacking: In quantitative research, exploiting techniques that increase the likelihood of obtaining a statistically significant result.
Post-hoc justifications: Researchers write up justifications for their actions after a study – these justifications were not planned or decided before the study happened.
Reproducibility: A study is reproducible if you are able to get the same results when conducting the same analyses on the same data as the original study.
Replicability: A study is replicable if you are able to conduct the same study again, generate new data, and still get the same results as the original study.
Selective reporting: Researchers are selective reporting if their results are deliberately not fully or accurately reported, in order to suppress negative or undesirable findings.
Systematic review: A structured literature review, which analyses existing research evidence according to a fixed set of criteria, then synthesises what the research evidence shows.
Week 4: Documenting Decisions Transparently
‘Between’, ‘within’ or ‘mixed’ study design: A ‘between’ study design compares different conditions between groups, a ‘within’ design compares different conditions within the same group, and a ‘mixed’ study combines the two.
Confirmatory analyses: Analyses set before data collection or examination: their role is to test hypotheses.
Counterbalancing: A technique used by psychologists to deal with order effects when conducting repetitive tests, giving half the participants the tests in one order, the other half in the reverse order.
Dependent variable: In a scientific experiment design, this is the variable that changes as a result of an intervention: the researcher is interested in recording these changes.
Experimental conditions: In a scientific experiment design, these are the factors that are controlled during the experiment.
Exploratory analyses: Analyses set after an initial data set and hypothesis have been generated: they are useful for discovering patterns in data, in order to foster hypothesis development and refinement.
Independent variable: In a scientific experiment design, this is the variable that the researcher manipulates in order to investigate its effect.
Preregistration: The practice of publishing the plan for a study, such as research questions, hypotheses, research design, or data analysis plans before the data has been collected or examined.
Registration: Some disciplines differentiate between ‘preregistration’ and ‘registration’, but the broad purpose is often similar.
Research degrees of freedom: The flexibility inherent in research, from hypothesis generation, designing and conducting a research study, to processing and analysing the data and interpreting and reporting results.
Week 5: Integrity: Supporting Robust Interpretations
Multiverse analysis: Systematically sampling a vast set of specifications, known as a multiverse, to estimate the uncertainty surrounding the validity of a scientific claim.
Positionality: Refers to an individual’s social and political position within society, including their identity, background, experiences, and beliefs.
P-value: A p-value is a statistical measurement used to validate a hypothesis against observed data. The lower the p-value, the greater the significance of the observed difference.
Preregistration: The practice of publishing the plan for a study, including research questions/hypotheses, research design, and/or data analysis plans, before the data has been collected or examined.
Reflexivity: An idea borrowed from qualitative research, reflexivity involves critical reflection on the researcher’s position and how it influences the research process.
Robustness: Refers to the strength and reliability of results.
Week 6: Accessibility: Making your research accessible online
Accessible research: Research is accessible if all who are interested can consume, evaluate, and otherwise interact with research products and processes.
Business models: A private company’s business model is the company’s plan for how it will make a profit.
Creative Commons license: A Creative Commons license enables re-users to distribute, remix, adapt and build upon the material, as long as they abide by conditions set by the author.
Integrity: The principle of integrity refers to the degree of trustworthiness or believability of research findings.
Open access: Open access is the free, immediate, online availability of research outputs such as journal articles without having to pay a fee, combined with the rights to use these outputs fully in the digital environment.
Preprints: Preprints are a way to ensure that your work is openly accessible to others, regardless of where you publish your research.
Transparent: The principle of transparency in research refers to the practice of being open and honest about all aspects of the research process.
Week 7: Accessibility: Academic privilege and diversity
Big team science: A research project in which researchers from around the world conduct the same study and pool their results.
Equity: Equity means the quality of being fair or impartial. In education, it is understood as presenting all scholars with the same opportunities, which sometimes requires making adjustments for their particular needs.
Privilege: Privilege is unearned access or advantage, which specific groups of people have because of their membership of a particular social group.
Sampling variation: The extent to which the data vary in different samples taken from the same population.
Week 8: Committing to open research
Preprint: An open-access version of your work (either before, after, or instead of publication in a journal) hosted on a preprint server.
Slack community: A slack community is a simple discussion forum, with different channels helping to organise separate conversations for specific subgroups.
Would you like to explore a comprehensive glossary of open scholarship terms? Check out the FORRT Glossary, a community-sourced glossary currently available in English, German, and Arabic.
