GLOSSARY

Definition: The tendency to report only significant results in the abstract, while reporting non-significant results within the main body of the manuscript (not reporting non-significant results altogether would constitute selective reporting). The consequence of abstract bias is that studies reporting non-significant results may not be captured with standard meta-analytic search procedures (which rely on information in the title, abstract and keywords) and thus biasing the results of meta-analyses.

2022 - FORRT > Framework for Open and Reproducible Research Training content licensed under a CC BY NC SA 4.0 license

Definition: From Latin meaning “to the person”; Judgement of an argument or piece of work influenced by the characteristics of the person who forwarded it, not the characteristics of the argument itself. Ad hominem bias can be negative, as when work from a competitor or target of personal animosity is viewed more critically than the quality of the work merits, or positive, as when work from a friend benefits from overly favourable evaluation.

2022 - FORRT > Framework for Open and Reproducible Research Training content licensed under a CC BY NC SA 4.0 license

Definition: This bias occurs when one’s opinions or judgements about the quality of research are influenced by the affiliation of the author(s). When publishing manuscripts, a potential example of an affiliation bias could be when editors prefer to publish work from prestigious institutions (Tvina et al., 2019).

2022 - FORRT > Framework for Open and Reproducible Research Training content licensed under a CC BY NC SA 4.0 license

The Agreement on Reforming Research Assessment is a declaration that commits its signatories to contribute to reforming the current research assessment system to make it fairer, more inclusive and focused on the value of research quality and impact. Its core actions include promoting the use of qualitative indicators, supported by responsible use of quantitative indicators, the recognition of the diversity of research outputs, and the abandonment of the inappropriate use of journal-based metrics and rankings. Unlike previous initiatives in research assessment, such as DORA or the Leiden Manifesto, the Agreement commits its signatories to implement these changes within an established timeframe (2022-2027). To support the reform, a Coalition for Advancing Research Assessment (CoARA) has been founded (see separate entry).

References & further information:

https://coara.eu/app/uploads/2022/09/2022_07_19_rra_agreement_final.pdf

https://coara.eu/ 

Anonymisation is the process of removing personally identifiable information (information that directly or indirectly relates to an identified or identifiable person) from datasets containing sensitive data. As a result, data subject is no longer identifiable. As opposed to pseudonymisation, anonymisation is not reversible, which means that the re-identification of the data subject is not possible.

Various digital tools that can automate anonymisation are available, e.g. Amnesia, ARX, Privacy Protection Application, etc.

Source: https://www.openaire.eu/how-to-comply-with-horizon-europe-mandate-for-rdm (Glossary)

ARGOS is an online tool in support of automated processes to creating, managing, sharing and linking Data Management Plans with research artifacts they correspond to. It is the joint effort of OpenAIRE and EUDAT to deliver an open platform for Data Management Planning that addresses FAIR and Open best practices and assumes no barriers for its use and adoption. It does so by applying common standards for machine-actionable Data Management Plans as defined by the global research data community of RDA and by communicating and consulting with researchers, research communities and funders to better reflect on their needs. 

Source: https://argos.openaire.eu/about

Article processing charge (APC) means the payment by the author (the funder, the institution or the employer) to the publisher in exchange for publishing and hosting an open access article. APCs are used by open access journals in lieu of subscription fees that libraries and readers traditionally have paid to gain access to research articles. Journal APCs vary widely, from about $300 to over $10.000, and diverse funding may be available. 

Reference: https://forrt.org/glossary/article-processing-charge-apc/ 

"Publication fees charged by certain open access journals post-acceptance, are also known as author publishing charges or article processing charges (APCs). APCs may be driven down by submission fees, particularly among open access journals with high rejection rates. In contrast to post-acceptance charges by traditional journals, these APCs are more often flat fees because they primarily fund peer review and online dissemination, which are length independent.

Be aware that “predatory” journals may take advantage of the APC-based model to receive payment in return for minimal peer review and processing, so be sure to look for warning signs and consider checking whether your target journal is listed by the Directory of Open Access Journals. A truly open access journal should also meet the two-fold requirement defined above by PLOS: “unrestricted access and unrestricted reuse,” meaning that an open access article must not only be freely accessible to readers but also freely available for copying, distribution, and derivative work, as long as the original author is acknowledged. In particular, open access articles are often associated with a CC-BY license, although certain journals may not support reuse/derivation."

An Author Accepted Manuscript (AAM) is defined as the version of the work as accepted for publication, including all changes made during the peer review process. This differs from the Version of Record (VoR), which is the version of a journal article that has been made available by any organization that acts as a publisher by formally and exclusively declaring the article “published”.

An example of the AAM being used as part of Rights Retention wording (in alignment with Plan S) in a submission to a peer-reviewed journal:

“This research was funded in whole or in part by [Funder] [Grant number]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript (AAM) version arising from this submission.”

AAM definition and further reading: https://www.coalition-s.org/rights-retention-strategy/

VOR vs AAM: https://scholarlykitchen.sspnet.org/2021/04/05/publishers-care-about-the-version-of-record-do-researchers/

The author's final, peer reviewed and corrected manuscript is the version of paper that has been updated to include all changes resulting from peer review, as well as any changes requested by the journal editor.
Authors are encouraged to use Sherpa Romeo (https://v2.sherpa.ac.uk/romeo/) to analyses publisher open access policies and to deposit their accepted manuscript in a right way to repositories, sometimes after an embargo period. 
AAM is usually created in Word or LaTeX document or similar and will not contain any publisher typesetting or copyediting.
The AAM is not the same as the publisher's PDF.

A license can be an agreement (a contract) between the licensor and the licensee including any freely negotiated terms. Such a license is sometimes referred to as a ‘bespoke’ license, or a custom-made. license. https://www.clarin.eu/content/clic-public-and-open-licenses

“Big Data exceeds the reach of commonly used hardware environments and software tools, to capture, manage, and process it within a tolerable elapsed time for its user population” (Merv, 2011)

“Big Data refers to data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze” (McKinsey Global Institute, 2011)

Big data refers to collected data sets that are so large and complex that they require new technologies, such as artificial intelligence, to process. The data comes from many different sources. Often they are of the same type, for example, GPS data from millions of mobile phones is used to mitigate traffic jams; but it can also be a combination, such as health records and patients' app use. Technology enables this data to be collected very fast, in near real time, and get analyzed to get new insights (European Parliament, 2021).

Big Data is different from traditional data sources:

1.      Big Data is often automatically generated by a machine

2.      Is typically an entirely new source of data.

3.      Many Big Data sources are not designed to be friendly (Franks 2012, p9).

European Parliament (2021). Big Data: definitions, benefits, challenges (infographics). https://www.europarl.europa.eu/news/en/headlines/society/20210211STO97614/big-data-definition-benefits-challenges-infographics

Franks, B. (2012). Taming the Big Data Tidal Wave. Hoboken, NJ: Wiley

Merv, A. (2011). Big Data. Teradata Magazine, 1 (11)

McKinsey Global Institute (2011). Big Data: the next frontier for innovation, competition, and productivity, May 2011

Definition: The CARE (Collective benefit, Authority to control, Responsibility, Ethics) Principles for Indigenous Data Governance are people and purpose-oriented, reflecting the crucial role of data in advancing Indigenous innovation and self-determination. These principles complement the existing FAIR principles encouraging open and other data movements to consider both people and purpose in their advocacy and pursuits.

Collective benefit
Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
C1- For inclusive developmet and innovation
C2- For improved governance and citizen engagement
C3- For equitable outcomes

Authority to Control
Indigenous Peoples' rights and interests in Indigenous data must be recognised and their authority to control such data be empowered. Indigenous data governance enables Indigenous Peoples and governing bodies to determine how Indigenous Peoples, as well as Indigenous lands, territories, resources, knowledges and geographical indicators, are represented and identified within data.
A1- Recognizing rights and interests
A2- Data for governance
A3- Governance of data

Responsibility
Those working with Indigenous data have a responsibility to share how those data are used to support Indigenous Peoples’ selfdetermination and collective benefit. Accountability requires meaningful and openly available evidence of these efforts and the benefits accruing to Indigenous Peoples.
R1- For positive relationships
R2- For expanding capability and capacity
R3- For Indigenous languages and worldviews

Ethics
Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.
E1- For minimizing harm and maximizing benefit
E2- For justice
E1- For future use

The current movement toward open data and open science does not fully engage with Indigenous Peoples’ rights and interests. Existing principles within the open data movement primarily focus on characteristics of data that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts. The emphasis on greater data sharing alone creates a tension for Indigenous Peoples who are also asserting greater control over the application and use of Indigenous data and Indigenous Knowledge for collective benefit. This includes the right to create value from Indigenous data in ways that are grounded in Indigenous worldviews and realise opportunities within the knowledge economy.

Related terms: FAIR Principles

Found in: "CARE Principles for Indigenous Data Governance". https://www.gida-global.org/care

References: Research Data Alliance International Indigenous Data Sovereignty Interest Group (2019). "CARE Principles for Indigenous Data Governance". The Global Indigenous Data Alliance. GIDA-global.org

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The European Citizen Science Association describes citizen science as follows: "Citizen science is an ‘umbrella’ term that describes a variety of ways in which the public participate in science. The main characteristics are that: (1) citizens are actively involved in research, in partnership or collaboration with scientists or professionals; and (2) there is a genuine outcome, such as new scientific knowledge, conservation action or policy change. (...) Citizen science takes place in diverse fields, including ecology, astronomy, medicine, computer science, history – and many more. And citizen science can happen at a range of different scales – from local projects to continental and global scales, and from short projects to those that occur over decades!"

ECSA "Characteristics of Citizen Science" 

Civic engagement refers to the active involvement of people in the life of their communities in order to provide solutions to social problems, improve conditions and so positively affect the future and prosperity of their community. Civic engagement is a term that remains open to various interpretations depending on the context it refers to. Overall, civic engagement is deemed a significant characteristic of a community whose members feel connected with each other and realize the importance of being actively engaged for the benefit of their community. In this context, the level of engagement varies depending on several factors, such as the distribution of power, the degree of social justice and the representativeness of people in the political arena.

Alternative definition: public engagement, public participation, active citizenship

References: Adler, R. P., & Goggin, J. (2005), Glas, N., Pelachaud, C. (2015). Ekman, J., Amnå, E. (2012).

The Coalition for Advancing Research Assessment (CoARA) is the organization to which signatories of the Agreement on Reforming Research Assessment (see separate entry) are optionally members. It has been created to support, guide, and monitor the implementation of the Agreement, and importantly serve as a platform for discussion, exchange, and cooperation among its members via the creation of Working Groups.

References & further information:

https://coara.eu/

Controlled vocabulary is an organised and standardised arrangement of predefined terms (words and phrases) that are used to index content in an information system with the aim of facilitating information retrieval. Controlled vocabularies provide a consistent way to describe data. They are standardized and organized arrangements of words and phrases presented as alphabetical lists of terms or as thesauri, ontologies, and taxonomies with a hierarchical structure of broader and narrower terms. Controlled vocabularies also connect variant terms and synonyms for concepts, link concepts in a logical order and organise them into categories. They can be general and discipline-specific. Using a controlled vocabulary will aid in searching and finding your data and will make your data more shareable with researchers in the same discipline.

Ontologies are not controlled vocabularies, but they use controlled vocabularies to establish a formal specification of a conceptual model in which concepts and categories of concepts, properties, relationships among concepts and categories, functions, constraints, and axioms are defined.

Registries of controlled vocabularies:

• https://bartoc.org/
• https://bartoc.org/registries

Sources: https://op.europa.eu/en/web/eu-vocabularies/controlled-vocabularies ; https://guides.lib.unc.edu/metadata/controlled-vocab, https://www.openaire.eu/how-to-comply-with-horizon-europe-mandate-for-rdm (Glossary)

Copyright (or author’s right) is a legal term used to describe the rights that creators have over their literary and artistic works. Works covered by copyright range from books, music, paintings, sculpture, and films, to computer programs, databases, advertisements, maps, and technical drawings.

source: WORLD INTELLECTUAL PROPERTY ORGANIZATION