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Inclusive Data Research Skills for Arts and Humanities/Deconstructing data methods and decolonising approaches

Defining the challenge, mapping out contexts and key stakeholders
When defining challenges, it is necessary to deconstruct and unpick the kinds of thinking, epistemologies and colonial practices that come with data tools, skills and methods. Embracing the collaborative and plural nature of a hackathon, we contextualised the relationship between coloniality and data methods through multiple perspectives and disciplines. We began to map out who the key stakeholders are, what are the core systems, institutions, frameworks we need to address.

1. Defining our key terms:
data

data methods

data epistemologies

coloniality

decoloniality

2. Reflections:
How do we encounter coloniality or de-coloniality from our lived experiences and/or within our particular disciplines? Where do data oriented computer tools or data practices come into this? What is the data being collected, who or what is being observed and who is observing, how is the data being labelled or categorised, what is the data used for?

How are data methods embedded within colonial disciplinary priorities and biases?
For instance: categorization, thinking in binaries, quantification, reduction, cultural privileging of “rational” science, the myth of ‘objective data’, the capitalisation of data, extractive data practices, bias, environmental extraction required for data processes to run.

Some of the areas discussed include:

 * Conversational generative AI is mostly trained on a western, capitalist, imperialist, patriarchal corpus and will drown out other voices
 * English mono-language based research
 * The prioritisation of written, digital, 'big' quantitative data
 * The distinction between right and wrong. In terms of education, decolonial methods in new schools are frowned upon or unsupported by the government a lot but helps students.
 * Difficulties putting theory into practice
 * Retroactively filling historical / research gaps. Revisionist thinking back and forward

How do the limitations of data or computational tools force certain worldviews or certain ways of thinking? Include examples of systems participants use within their field.
E.g. AI, search engine systems or research databases, social media analysis tools, facial recognition systems, surveys and questionnaires offering limited identity categories

 * How can we value, recognise, perpetuate and build upon data from non-written groups such as indigenous and first nation peoples?
 * "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" - by Bender et al, 2021
 * If it can't be connected, it doesn't matter
 * The area (geographic), assumptions, healthcare services, neurodivergent people, education system in the UK which is a settlement country, often majority of education is only in english.
 * online, computer and technological sources
 * Geographic Information Systems (GIS) have no room for qualitative data
 * How can we integrate indigenous methodology and alternative methodologies into canonical methods taking a BOTH, AND approach?

Who are they key stakeholders / players involved in colonial data methodologies? Who and what are we needing to address when we approach these challenges from a decolonial lens?

 * Data method researchers, The domain knowledge experts, Data recipients
 * Sponsors, curators and participants (data gatekeeping), transparency, supportive of people, collaboration, building trust, reciprocation.
 * Myself, UKRI, renewed use of hidden discriminatory parameters
 * acknowledging stakeholders "sociological imagination" and their validity as researchers. THE ETHICS OF STORYTELLING
 * managerial data people, knowledge hoarders, 'insight' commercial companies and more
 * people in positions of power to influence such methods

DATA GAPS / ABSENCE
''E.g. research gaps, theoretical gaps, access to computation and data. Do we need to fill gaps or how can they be useful? HI-RES/LO-RES BIAS certain geographical locations have concentrated data and concentrated technologies''

Some points of discussion included:

 * Participation of marginalised groups as practitioners and theorists
 * How can we teach, educate and create a decolonial framework in a society that is largely colonialist?
 * Invisible Women by Caroline Griado Perez really highlights the manifestation of such gaps
 * Revisiting methods and theories that are currently in use
 * gaps in data lead to a half-told truth. More inclusivity and plurality in data collection, storing and analysing will lead to filling gaps.
 * Parachuting in design. Be more available in terms of interaction, don't judge, be a facilitator not an expert
 * Creatively fill and show diversity in life experiences

Alternative Lens, mapping out key approaches and movements
What does a decolonial lens look like when working with data? What can we learn through examining the broad approaches different groups are taking in order to counter hegemonic powers?

Themes and approaches include:

Participatory Action Research / Co-design

 * Data Walks Alison Powell
 * Ethnography
 * Citizen Science eg. IMPETUS
 * Role playing and games
 * Equity film making
 * Any method that redresses or aims to redress the imbalance between powerful researcher extracting data from data subjects
 * Action research
 * Using your own body as a site of research, self-realisation
 * Utopia
 * Design imaginaries

Democratising access to design tools and skills

 * Decolonizing Reader (resources)_Collaborative (open) edition
 * Github, open source, open access, open data
 * Low tech approaches - drawing data
 * Creative non-tech approaches to data literacy through the arts and community eg Data Murals
 * MediaFutures Toolkit - focusing on AI/art interactions but with lots of lovely open access data tool resources

Pluralist lenses

 * Indigenous voice
 * TEK (traditional ecological knowledge)

Using data/ creating datasets for justice

 * Atlas of Environmental Justice - documenting global environmental conflicts
 * Data For Black Lives - “Data for Black Lives is a movement of activists, organizers, and scientists committed to the mission of using data to create concrete and measurable change in the lives of Black people”
 * Decolonial Atlas

Social movements, worker movements

 * Algorithmic Justice League
 * 'No Tech for Apartheid' and ‘#TechWon’tBuildIt’ campaigns by Tech Workers Coalition
 * “The  Alliance for inclusive algorithms is organized by Women@theTable and Instituto Tecnológico de Costa Rica (TEC). It’s a global, multidisciplinary, feminist coalition of academics, activists, technologists, prototyping the future of artificial intelligence and automated decision making to accelerate gender equality with technology and innovation.”

Frameworks for alternative thinking

 * Design Justice Network principles
 * Data Feminism by D’ignazio & Klein
 * Arturo Escobar’s ‘Designs for the Pluriverse’ which argues towards 'design for transitions' and 'autonomous design'
 * Pluriversity as a way of teaching and knowing Indigenous methodologies and values.
 * Feminist Data Set (Caroline Sinder)- Is each step feminist? Is it intersectional? Does each step have bias? How can that bias be removed?
 * Designing with the future
 * Machine consciousness
 * Data Justice - eg Couldry & Meijas (2018) or Laura Mann
 * “Both/ And” Approaches to knowledge production, to reject notion of binaristic system
 * “Walking while asking questions” - Zapatistas motto, democratic potential within decolonial thinking
 * Bringing feminist perspectives into community informatics by Peddle, Katrina, Powell, Alison and Shade, Leslie Regan (2008)

Counter-Investigation
Groups using data methods to hold hegemonic powers to account, whilst also reflecting and making aware the biases embedded in such tools.

 * Forensic Architecture's methods of constructing political narratives for a place using digital tools to create digital tours and exhibitions, for instance in their project 'Sheikh Jarrah: Ethnic Cleansing in Jerusalem'
 * Forensic Architecture's 'Conquer and Divide' interactive web platform to retrace the occupation of the Westbank and Gaza
 * Forensic Oceanography
 * INTERPRT
 * Future predictions and DATA (trend-forecasting)

Education / Pedagogy

 * Color Coded LA: ‘We are a POC-only space and collective co-teaching, co-creating, and co-owning new technologies
 * Free schooling
 * Bermondsey Lampposts case study
 * Collective Design School
 * Multilingual children’s support
 * Criticising Decolonising the University

Critical arts projects:

 * Mimi Onuoha’s ‘Library of Missing Data Sets art project
 * 'The Work of Art in the Age of Artificial Intelligence: What Artists Can Teach Us About the Ethics of Data Practice' by Kate Crawford
 * Media Futures projects
 * 'AI Art and Misinformation: Approaches and Strategies for Media Literacy and Fact Checking' by Walker, Thuermer, Vicens, Simperl, 2023

Abolitionist perspectives on technology:
When data / technologies prop up military and policing, it is argued these practices can never be decolonial, so abolitionist principles may be a framework to think through these.

 * Carceral Tech Resistance Network: ‘organising against the design, experimentation and deployment of carceral technologies’
 * The Surveillance Technology Oversight Project: working to end discriminatory surveillance
 * Digital freedom, Digital rights, Digital Human Rights discussed by UN Interagency Dialogue on Disinformation and Data Transparency
 * Responsible AI
 * 'A world without Data' Blog

Co-created resources:
The following pointers are suggested principles and reflective questions for researchers/students to approach decoloniality when working with data methods.

The task of decoloniality is always changing, this is not a definitive set of answers.

Key values that need to be central when approaching challenges:

 * Criticality as an approach
 * Contextualising and considering the historical background in which data have been selected or extracted and then analysed with personal biases and filters. Thinking in terms of working with data is a reflection about when, how, how data was collected and stored, and who collected it. (Marika/Art practice and research)

Create a loose set of guidelines/principles for arts and humanities projects working with data methods for how to challenge coloniality.

 * Elasticity, creating flexible guidelines and principles that can be welcoming and inclusive for under-represented, under-considered data, and their provenance. And also in terms of future thinking, and how to adopt and support the raising of diversity of needs.
 * Developing a set of key values:
 * Reciprocity ← key when thinking about non-extractive data processes
 * Based on social justice principles: access to resources, participation, equity and human rights
 * Equality of privilege - low tech artisanal lived experience data is valued equally with high tech computational big data

What are some critical questions to prompt reflection on projects in relation to decoloniality?

 * Why am I doing this?
 * For whom am I doing this?
 * Who does this serve?
 * Who is benefitting from this?
 * In what aspects of the project reflect decoloniality?
 * Where do they might come from: technical or theoretical problems?
 * Whose voice is being heard?

What practical and technical tools do we need?

 * (Positionality: Design researcher working with communities)
 * Practical tools could range from the decolonial ideologies of working ‘with’ and not ‘for’. Unlearning: decolonising means a lot of unlearning and learning, where there might be a completely flipped version of accessing and transferring data.
 * Intersectionality.
 * Empathy
 * Certain level of cultural, socio-political understanding and linguistic ability of the topic of research

What perspectives, thinking tools, frameworks, theories do we need to engage in decoloniality?

 * Pluriversal / pluriverse / pluriversal thinking
 * Both / And
 * Perspectives - accessible intros to standpoint epistemology, intersectionality, the gaze, etc that can tap into people’s lived experiences
 * Real engagement with data itself and data tools so that conversations can move from critical ‘hovering over’ of the academic eye to questions around empowered ways to work with data – not just as a data subject, but a ‘data agent’ (not sure what it should be called because in reality we become ‘data workers’ which is not necessarily at all empowering. So there seems like some tension between acquiring data skills as empowering and becoming a data worker as falling back into less agential roles. Or something like this!
 * A side note on LLMs (large language models) and ethics
 * Conversational generative AI such as ChatGPT, Bart etc offers a really exciting opportunity for the co-analysis of qualitative data. However, ANYTHING you put into a GPT interface becomes training data for that product. It is therefore crucially important to get INFORMED CONSENT from anyone whose contributed data (anonymous or not) you intend to put into a chatbot. This informed consent includes telling them that their data will be retained and used as training data.They may be fine with this! But they need to know.
 * You may also find that your institution’s data protection rules require you to declare if you are sending data outside of countries with EU GDPR parity. Open.AI’s servers are based in the US.
 * Data Justice Plan Template This was created by Johanna Walker & Gefion Thuermer after we had worked on several EU projects which used cascading funding to support small to medium enterprises to develop smart cities products and services using citizen data. Where data is silently and invisibly collected by sensors and manipulated by algorithms, civil society is at risk of being simultaneously used as the subjects and objects of data, yet with no guarantee of receiving its benefits. This is a form of data injustice, where the benefits of data flow in one direction and are not evenly or fairly distributed. Data that is collected with citizens as its subject or object  should benefit the community that it came from. Think about how you can ensure that this happens for your project data.
 * Who will contribute data to your project/artwork, and why?
 * How will they benefit from what you plan to do with the data?
 * How will this benefit materialise?
 * Who will be responsible for making this happen?
 * What will happen if the project/artwork does not go to plan – what can participating communities benefit from partial results, or what additional results might become available?
 * Who else will benefit from the data and how? We have also been testing this template with data artists.


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Inclusive Data Research Skills for Arts and Humanities/What counts as data?

In an arts and humanities context, what counts as data can be any observable traces of interactions and occurrences. In arts and humanities research, any of a vast and complex set of recordable observations and artifacts fit into some definition of “data”, and the contextual issues around their interpretation depend on the form of data that is being dealt with. The following page is an attempt to provide broad categorisations and distinctions between different kinds of data, and address some of the challenges in their use.

The absence of data also constitutes data (was something destroyed or lost, is something disregarded or in a foreign language or physically/digitally inaccessible, etc.).

Potential Categorisations
Data categorisations are influenced by a variety of factors including research objectives, research questions, research design, existing standards within a specific discipline, approaches to information interpretation, nature of sources of information, and psychological connotations, among others. How researchers collect data also plays an important role in how this data is then perceived, categorised and analysed.

Qualitative and quantitative data
Researchers’ objectives determine the methods used and approach to data. Depending on the aims of the research and research questions, data could fit into qualitative and quantitative categories. For example, surveys can provide both qualitative and quantitative data depending: what % of people answered yes or no to certain questions? OR describe, interpret and contextualise each response.

Qualitative

 * Oral histories and interviews
 * Archival text
 * Artwork and media objects
 * Free text responses to surveys

Quantitative

 * Website analytics
 * Census records
 * Datasets

Analogue and digital data
The nature of the sources of data determines if we can classify data as analogue (physical) or digital.

Analogue Data - Trace of interaction with the surrounding world through time.

Research objectives and questions also influence the classification of data as analogue or digital. For instance, a book historian analysing a digitised version of a manuscript would consider it to be a source of analogue/physical data, while a researcher analysing the level of digitisation of a collection would most likely consider it to be a digital source.

Analogue/physical:

 * artworks/objects,
 * books,
 * manuscripts,
 * documents,
 * photographs,
 * slides,
 * Negatives,
 * Maps
 * Desire paths

Digital data:

 * Website analytics
 * Digital scans of physical/analogue items
 * Videography
 * Films / documentaries
 * Digital files of photographs
 * Comments from social media
 * E-books
 * Voice records
 * Datasets
 * Online / app usage

Subjective

 * Autoethnographic data
 * Opinions / perspectives
 * Diaries
 * Cultural background differences
 * Physical ability
 * Experiential data

Objective

 * Census records (for certain demographics and when answering specific questions within traditional, pre-existing societal categories)
 * Materials, ie that constitute an artwork
 * Chemical analysis, X-ray, etc.

Datasets

 * Kaggle.com
 * Google.com
 * Kanopy.com
 * The British Library
 * Museums
 * Office for National Statistics
 * Government data (from data.gov.uk)
 * People (through interviews/surveys)
 * Office for National Statistics
 * Police Data
 * UK Data Service

Online archives

 * Bishopsgate Institute
 * New York Public Library
 * Discover Europe’s digital cultural heritage | Europeana
 * Images search | Wellcome Collection
 * Courtauld Gallery Online Collections
 * Social-networking photo sharing platforms like Instagram, Facebook, Twitter etc.
 * The Met Museum

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Inclusive Data Research Skills for Arts and Humanities/Data Visualization

https://docs.google.com/document/d/1YtF1zgLYFd_YpS2AVXE7UxbWaYS3BJpYTSU3GPY8_PY/edit

Definition(s)
Data is not just numbers but information (Gitelman, 2013)

What is data visualisation?

Data visualisation is the process of interpreting information through distinctive and contextually relevant concepts and translating the data into a visual narrative.

It connects readers to insights, knowledge and power, and it can generate new relevant questions.

Medium to

 * 1) Explore: analyse, engage, interact, reflect
 * 2) Discover: find insights, knowledge, ideas, connections, gaps
 * 3) Express: interpret, narrate, explain, guide attention, storytelling

Why is it valuable for A&H researchers?

 * 1) Creative Process  Transforms research and collection of information into visual expression

 * 1) Product of that process / Outcome  Presentation of the findings and presenting new questions

Data
Data gathered in the course of qualitative research can vary dramatically depending on the subject of investigation. For example, data can be gathered through discussions, interviews, observations, photographs, painting, video and audio. This can pose both a challenge and an exciting creative opportunity for the qualitative researcher.

It is also important to remember that the interpretation of qualitative data can be subjective. It is therefore important to consider your own positionality and bias when embarking on data visualisations.

Data visualisation in research
Data Visualisation is used in multiple ways within arts & humanities research, for numerous purposes. This can include visualisation of both qualitative and quantitative data, however within arts and humanities particular consideration is needed regarding visualisation of qualitative data. Whilst qualitative data can be translated into categorical or numerical data, there is a balance to be struck between simplifying the richness of a qualitative dataset and capturing its complexity for the purposes of visualisation. Within arts & humanities data visualisation is used for distinct purposes beyond graphical output of research outcomes and can inform processes of discovery and the research journey.

These purposes should not be seen as distinct, as they interact with each other, and also interact with other phases of the research journey including research outcomes.

Purposes of data visualisation include:

 * Collecting:  bringing together information from multiple data sources
 * Synthesising:  identifying connections between multiple data sources / different types of data into one visual array
 * Exploring:  Processes of data discovery including pattern identification, Comparison, Visualising change over time
 * Analysis: Identifying sources of missing information / gaps in data eg who / what is not represented
 * Experimentation: considering what is the best way to understand the data? How could it be communicated?  What happens if the scale is changed or the data is configured differently?
 * Narration: Using visualisation to explore what story the data may tell, particularly those that may be different from the stories we expect
 * Displaying results
 * Distilling - making choices about key themes / pulling out particular ideas
 * Communication - using data to capture attention or share information in unusual and informative ways
 * Inviting feedback - using visualisation as a means of engagement and capturing reflections / responses from an audience
 * Generating further research questions - using data visualisation to inform and shape further stages of research
 * Supporting interdisciplinary conversations - using data visualisation as a means of communicating across boundaries

Data visualisation as an outcome
Data visualisation can be used to tell a story narrative; presenting information in a way which is accessible to the wider public. This is particularly important when exploring nuanced or complex questions or topics which a layperson may be unfamiliar with.

Benefits of data visualisation:

 * Accessibility: Data visualisation can be used to connect with audiences who are unable or unwilling to read raw data
 * Engagement: Data visualisation can gamify information and in doing so reach a larger audience
 * Interaction: People can explore data at their own pace and seek out the information that interests them
 * Empowerment: Making data more accessible can empower others to do their own research or take action within their own communities

When visualising your data, it is important to consider what your priorities are. If the goal is to make information as accessible as possible, this may affect how and where you present your data. Creating your own website may be a compelling idea but this requires continuous funding/resources. Will a website of your own design still be accessible in five years time? When possible, data can be made open to improve accessibility. You may want to consider sharing data you have collected on sites like Wikidata.

Visualising data can also be beneficial for the researcher by providing them with the opportunity to reflect on their research. Gaps in data can be identified and new questions can be raised.

Improving data visualisation
Visualisation of data for un/underrepresented groups when the baseline for that data collection is ‘0’ might start from below the lowest data point to allow the visualisation of a lack of data. Missing data can be visualised by a showing of the lack of data, generally demonstrated through spatial or visual gaps and juxtapositions within data visualisations.

Qualitative data is often visualised through methods of quantifying qualitative information. We should find new ways of visualising or interacting with data through qualitative means. Chord, network, and Venn diagram charts may be a few ways of doing this effectively, but what are other innovative ways that we may view qualitative data? How might other modes of engagement be used to understand this data (i.e. sound, touch).

Something here is needed about using multiple visualisations to engage in varied interpretations.

Information we collect

 * Multiple auto/biographical statements (convergent narratives)
 * Movement data
 * Sound/music
 * Historical (longitudinal)
 * Crowdsourced

Tools we're already using
Tools used to collect, code, analyse, explore, and share:

 * augmented or virtual reality

 * Recordings (images, videos, sound)
 * Drawing - e.g. Notation (movement)
 * Excel
 * 3D
 * AI
 * Auto Ethnography
 * Nvivo (textual analysis)

Challenges within data visualisation

 * Complexity of narrating and storytelling
 * Subjectivity of Data
 * Interpretation and Ambiguity
 * Cultural Sensitivity
 * Understanding de/colonial narratives of data
 * Ethical Considerations
 * Technical Limitations
 * Digital Gap
 * Urban vs. rural regions
 * Generation-conflict
 * Developed vs. developing countries
 * Data Literacy
 * Aesthetic Considerations
 * Translate humanities research into the logic of database
 * New tools, digital and analogue
 * Accessibility (disability standards)


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Inclusive Data Research Skills for Arts and Humanities/Data practices

Object of study > Data Problem(s)


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Philippine History/Prehistory

Homo luzonensis, also locally called "Ubag" after a mythical caveman, is an extinct, possibly pygmy, species of archaic human from the Late Pleistocene of Luzon, the Philippines. Their remains, teeth and phalanges, are known only from Callao Cave in the northern part of the island dating to before 50,000 years ago. They were initially identified as belonging to modern humans in 2010, but in 2019, after the discovery of more specimens, they were placed into a new species based on the presence of a wide range of traits similar to modern humans as well as to Australopithecus and early Homo. In 2023, a study revealed that the fossilized remains of the Callao Man has been found out to be 134,000± 14 years old and much older than previously known.

title: Philippine History/Prehistory


text: Philippine History/Vice-Presidents

title: Philippine History/Vice-Presidents


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Inclusive Data Research Skills for Arts and Humanities/What kinds of research can data-oriented arts and humanities researchers do and what are the possible challenges?

Data-oriented arts and humanities researchers can:
Digital and data skills are becoming increasingly important parts of the arts and humanities. These kinds of data that have always played an essential role in Arts and Humanities are available in digital formats. Equally, the lives of everyday people are now played out in ways that develop digital data, creating new sites and opportunities for arts and humanities research. In terms of arts and practice research, data can play a crucial role in many forms of digital art, making digital and data skills a valuable tool for creation of new art and insights.

Using digital and data skills, Arts and Humanities researchers can:

 * Analyse and critique the assumptions that underlie big data-sets
 * Invent new ways to visualise data
 * Understand how people use social media
 * Share ways of understanding data that do not come from colonial perspectives

Arts and humanities researchers can also use their knowledge of data and digital skills to question those skills using the knowledge of data as a way of pushing back against assumptions and biases of technology and technology-based research. "Digital and data skills can be tools of resistance."

Some of the challenges are:
While digital and data skills can provide many opportunities for arts and humanities researchers, there are also some challenges. Over the course of the DAReS project we have identified some of these challenges, and where possible started to look at ways of addressing some of these challenges.

While there are specific challenges, one of the difficulties can be with regard to culture and language. This is a twofold challenge; on the one hand, those from a science, technology or data background may use specific disciplinary language and have an expectation of background using computers, maths and programming. While this background isn’t needed, for example, learn to code in Python.

On the other hand, language and culture can be challenged when working with data, as most data is collected from a Western colonial perspective and may only sometimes inherently create space for alternative viewpoints. As arts and humanities researchers, we can bring our knowledge and expertise of critical perspectives to data research as a way of questioning and interrogating the data – this is done with more authority when speaking from a place of having sufficient knowledge of the skills and tools.

Other challenges can be: Some of the core ways of overcoming these challenges include:
 * Lack of skills to manage a lot of data
 * Lack of technical skills (from creating pivot tables to coding)
 * Not knowing where to find data sets
 * Understanding how to ask the kinds of research questions that can be answered by data and through data skills
 * Multi and interdisciplinary work is inherently really difficult, right from coming up with the right question to analysing and writing up the data

 * Networking: being engaged in data and digital research does not mean arts and humanities researchers need to become experts in the tools themselves. However, building connections with peers with interests and knowledge in computing and informatics is a way to co-create projects
 * Attending interdisciplinary conferences and workshops where there is space to tackle some of the issues you are trying to address.


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Inclusive Data Research Skills for Arts and Humanities/Who can potential collaborators, partners and team be?

Collaborators and Partners- getting the team together
Partners, collaborators and team members for data research projects in the arts and humanities could come from many places. They could be:

 * Other researchers, within your discipline or from another discipline
 * Community researchers (broadly meaning, anyone engaged in research outside of university contexts, who may or may not have research training)
 * Businesses
 * Not for profit organisations
 * Artists
 * Students

Like any other research project you want to bring together the group of people who are best suited to the goals and process of the project. Data research projects in the arts and humanities often inherently involve a certain amount of working across disciplines and methodological approaches. This is something to be embraced.

In addition, look at the funders and their funding priorities and then make connections with potential academic and other partners that can boost your credibility and endorse your creative practice. Especially for those at the start of the research journey.

Contacting Collaborators of and Project Partners
Projects often emerge organically, and in those cases, you may already have partners and collaborators in mind. A research project can be a great way to develop a research relationship, build new skills through collaboration or explore a new disciplinary area of research.

One of the best first steps in building your research team is to develop a single-page summary of your project. This should be seen as a working document that can develop over time. It is important that when you are bringing new people on board, you do not overly ‘nail down’ the research project so that the project can benefit from the wide range of expertise in development as well as execution.

When writing this initial one-pager there are a few things to consider:

 * 1) Avoid including confidential or sensitive information in this document; the purpose for this is to be shared; you don’t want to have to worry about it being passed to new potential partners.
 * 2) The documents should include information about what the potential funder is looking for (For example what funding call you are applying to) and the potential size of the project – a partner may feel differently about collaborating on a £500K project v,s, a £50K project with a junior researcher.
 * 3) Focus on the broad research question, methods and disciplinary grounding (lit-review), and demonstrate you already have the skills and expertise to execute the project. If there are gaps in the team, highlight these and how you will fill them
 * 4) Include an indicative work plan or timeline or Gantt chart; this will help the partners know how the project might fit with any existing projects or plans they may have.

Collaborators
Collaborators will include the people who make up the research team, these may be Co-investigators, consultants, researchers or have other titles depending on the funder. Working on research in collaboration can be very rewarding and lead to new findings and outcomes that might not be possible working on your own. Collaboration can be a great way to benefit from senior researchers’ experiences, and it can be an opportunity to mentor junior colleagues, who may bring new energy, approaches and enthusiasm to a project.

When building a research team a few things to consider are:
1)        Ensure diversity of experience and backgrounds – this is important for inclusion but also avoids groupthink.

2)        Start with contact you may have a relationship with first, or ask for an introduction through your networks, emails out of the blue are often missed.

3)        Think about any skill gaps your team may have, and consider who you would like to fill those gaps.

4)        Work across institutions and geographic areas as this can significantly broaden the scope of your project.

If you are applying for UKRI fuinding, once you have built your team you will need to compete a R4RI which sets out why your team has the skills you need for the project.

Project Partners
Project partners refer to organisations with a stake in the project but not part of the core delivery team. For UKRI grants, specifically, project partners must materially support the project (through support in kind) but cannot be directly paid for by the project. You can generally provide things such as travel, accommodation and subsistence if you need them to attend meetings, workshops or similar.

As part of your grant application process, you will need to ask your project partners to write a ‘letter of support’ which states why the project is relevant to their organisation, why they think it is worth supporting, and what material support/support in kind they will be providing.

Project partners can help you shape your project, ensure there is a clear pathway to impact and give you new access to key communities relevant to your project. It can be very useful to contact partners early in your process as they may have insight into how to make the project stronger, including making it more relevant to their work and more more likely to have an impact.

When planning your project make time to meet with potential partners as they may have questions or input, and while not every potential partnership pans out for the specific project, these initial conversation can be essential to future collaboration.


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Inclusive Data Research Skills for Arts and Humanities/How do you get funding?

There are various ways to get research funding for arts and humanities researchers. One of the main funding bodies for this field is the Arts and Humanities Research Council (AHRC), who have various funding rounds for different purposes

Where can I find previously funded projects?
Exploring previously funded projects is a great way to discover the types of projects that have been funded. The UKRI gateway (2024) to publicly funded research and innovation is an interactive tool with a search function. Users are able to search for projects by key words, subject, project team members and the project reference. Each project then includes:

UKRI has a ‘funding finder’ for searching current opportunities; this is a great place to start looking for funding. Some of these opportunities are very specific, others more general. You can also contact UKRI if you aren’t sure if your project is right for a specific research call.
 * Project title
 * Lead research organisation
 * Department name
 * Abstract
 * Organisations linked to the funding
 * People on the funding
 * Funded value
 * Funded period
 * Funder
 * Project status
 * Project category
 * Project reference
 * Principle investigator
 * Research subject
 * Research topic

As UKRI is a publicly funded body, all the projects that successfully received its funds can be searched; on this page, you can see who was involved in this project and what institution they were part of when the project was initially funded.

https://gtr.ukri.org/

Finding UKRI Funding
UKRI has a ‘funding finder’ for searching current opportunities; this is a great place to start looking for funding. Some of these opportunities are very specific, others more general. You can also contact UKRI if you aren’t sure if your project is right for a specific research call.

https://www.ukri.org/opportunity/

Overview of AHRC open grants
As part of the DAReS project, our post-doc researcher prepared this presentation about AHRC ‘open grants’; this can be a good place to start looking for applying for funding and thinking about what stage of research you are at.

research funding presentation


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Inclusive Data Research Skills for Arts and Humanities/What should a research goal be?

What a research goal is not.
In most cases, researchers set goals that are synonymous with a research objective, which is something that sets the destination for the research project itself. These could be thought of as “What does the research aim to achieve.”

A research objective needs to follow certain constraints and be agreed upon by all research team members. This could also be a more general statement of the Research Question or hypothesis, generally setting out the direction of travel. This kind of research goal can be helpful as it can help the research team determine what the research outputs and outcomes could be.

There is a danger with setting out your destination when starting a research project. As the research object is separate from the research questions, the research objective might anticipate the findings of the project, rather than being open to a range of outcomes from the Research question of hypothesis.

'''Research Outputs can be thought of as (what are the endpoint and work backwards). What is the research trying to achieve?'''

- Social impact

- Economic impact

- Innovation

- Pedagogy

Your research proposal doesn’t need to address all of these!

Research Goals as part of a Research Journey
Thinking more about something more like a research journey, the research goal is something a little different. Most research goals answer the questions ‘what’ or ‘how’ of the research; “What will we find out?” “How will we conduct the research”.

Instead, think of the research goal as a question of ‘Why” and, more specifically “, Why is this important?”. It is even possible to think of the research goal as, more importantly “, Why is this research important to you?”

Pushing back against the objective stance in research, your research goal can be a way of thinking about what makes the research personal to you as a researcher. This can mean that different members of the research project might have different research goals, and that is fine, even good. The research goals can recognise, that as well as researchers, you are also an individual, a person.

Your research goal might be:

“Working with a new researcher or research group.”

“Working with a new partner”

“Learning a new technique or tool, or exploring a new discipline.”

“Conducting research in a new geographic area.”

Why Research Goals?
Approaching the research goal in this way, is that you can sperate your success (and a personal evaluation of success) away from outputs you as a researcher might have less control over (paper publications, conference presentation, or even answering the research question). As part of your research journey, your research goals is about moving forward on that journey.


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Inclusive Data Research Skills for Arts and Humanities/Guidance on accessibility and good practice

Access is complex and there are multiple approaches to understanding it. Ellcessor (2016) writes:"First, access must be understood not in terms of availability, affordability, or choice but in terms of an individual’s ability to engage meaningfully with a medium/technology and its content; second, a hegemonic user position is created by digital media technologies and their usages, and this user position is not neutral but perpetuates an able-bodied norm and contributes to inequalities of access."By this Ellcessor places emphasis on meaningful engagement. Metaphorically, people cannot just be allowed in, they must be able to participate. Second, Ellcessor (2016) draws attention to the fact that digital technologies assume a particular user - usually a white, non-disabled, man. Good inclusive practice means not making this assumption.

In addition to accounting for a wide range of users and experiences of the world, good access practice understands accessibility, as practiced within disability communities, as a world-making practice that reshapes the material, digital and social world. Access is not a friction-less, self-evident good, that integrate disabled people into the non-disabled world without questioning the utility and ultimate good of that world.

More practically, the first and often most effective tool of access is always communication. Providing whoever you engage with, whether students, other researchers, the public or partners with clear information about where you'll be, what you'll be doing and what will be expected of them is a great starting point. This requires you to think carefully about the assumptions that you make what is involved in an activity. Those assumptions are likely embedded in your culture and quite possibly your assumptions about how bodyminds work.

Make sure you've given yourself a lot of time before the thing you are doing. There has to be time for conversation. Then, ask people what they need. Access can be expansive. This can go beyond how people's bodyminds do and don't conform to societal functions. Asking what people's access needs are can be as simple as asking, 'what do you need to do your best work'? Then respond, as best you can, with grace and curiousity. Access often challenges our deeply held and felt understandings of what 'good work' and 'politeness' is. This is challenging, but also part of the joy of access world-making.

In digital spaces, Wikimedia is pretty accessible. But all that work to build an accessible website doesn't count for anything if you don't write the alt text. Write the alt text.


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Inclusive Data Research Skills for Arts and Humanities/What is the research journey?

What is a Research Journey?
If we use "journey" to describe the act and practice of research, then it is logical to assume that the researcher/active subject is travelling within a landscape of knowing. Therefore, building a local body of practice accumulates contest knowability constantly.

If we define a body of knowledge as a community of people contributing to the practice's continued vitality, application, and evolution, then the 'journey' of the research is terra-forming, worldbuilding or architecture. Boundaries of knowability and practices must exist in forming this container of 'known'. In Art and Design, practice-based research methodology is widely practised, debated and redefined. It is conventional to consider the duration of practice as a key factor in moderating the hierarchy of competency and accept its vulnerability to social prejudices.

In Art and Design, practice-based research methodology is widely practised, debated and redefined. It is conventional to consider the duration of practice as a key factor in moderating the hierarchy of competency and accept its vulnerability to social prejudices.

Data, according to BBC Bitesize, is raw facts and figures that make no sense or do not have meaning. Data is words, numbers, dates, images, sounds, etc., without context.

In this definition, we must establish an esoteric typology for data in art and design research and research methodologies. The methodology to develop this emergent typology has to place iterative and reflexive deconstructions and reconstructions of standard practices in existing data science and data analytics.


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Inclusive Data Research Skills for Arts and Humanities/Self Sustaining Community of Researchers

A Community of Researchers
We are developing a community of researchers to continue the work started by the DAReS project.

Reading List: Data and Digital Research Skills for Arts and Humanities Researchers
As part of the community in which we are developing, we have created a reading list that may be helpful for thinking about work related to this project.

Conferences and Opportunities
Please add any conferences or opportunities that are relevant to the work of this book


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Inclusive Data Research Skills for Arts and Humanities/Storytelling

Storytelling is at the heart of everything we do as artist-researchers. We have explored together how data can tell stories and about data positionalities as well as data discrimination, and there is more work to be done on how we make the storytelling around data as transparent and open as possible...


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Walking Rugby

Walking Rugby is a much gentler version of the physically demanding game of Rugby. It is played on half of a normal pitch, participants must be walking at all times, and there is no tackling involved, instead a touch of two hands below the armpit or above the waist is used.

In some ways, it can be seen as similar in concept to Walking football or Walking netball where for whatever reason people cannot play the normal high-speed full-contact version of the game they are based on, in this case Rugby union

It is a good cardiovascular workout and can also help to improve speed, agility, and strength. Plus, it’s an opportunity to meet new people without the risk of getting tackled to the floor, if you don't what to play the outdoors, walking sports like this can be played inside all year round

Contents

 * /Introduction/
 * /Rules/
 * /Guidelines/

title: Walking Rugby


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Walking Rugby/History

Walking Rugby (WR) was started at Reading RFC in late October 2015, in response to enquiries locally to the rugby club regarding the possibility of a game similar to Walking Football which seems to have taken off nationally with some success.

Reading WR started with a group of about 8 to 12 people, initially at the Reading Rugby Club on grass, but soon moved indoors to a local sports hall. The group consisted mainly of retired members of the Rugby Club plus others with the flexibility to manage their own working hours. The version of the game that was started was very soon modified, adapted, and has evolved into the current version which we have tried to make identifiably a version of the game of Rugby Football Union.

title: Walking Rugby/History


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Walking Rugby/Rules

No running – walking determined by one foot on the ground at any time when in motion No contact – similar to ‘touch rugby’ rules – two hands on shorts is all the contact made which qualifies as a tackle. No Mauls or Rucks or Lineouts Scrummaging – max 3 players per team stood upright and non-contested. Passing backwards or lateral – offside rules apply A try requires no bending – you walk across the try line ball in hand.

The Main Rules of Walking Rugby

 * The game is split into four 5-minute (or longer by mutual team agreement) quarters, with 2-minute breaks for rehydration between each
 * Up to 7 players a side, with rolling substitutes
 * Players must not run or jog while the game is in action
 * The ball must be passed backwards or sideways but not forward
 * A try is scored by carrying the ball with both feet over the try line
 * "Knock-on" if the ball is knocked forward and hits another player or the ground, a deliberate knock-on is a penalty
 * Turnover if the ball hits the ground going backwards
 * Tackle is a two-handed touch to the ball carrier (shoulders down to shorts, including arms)
 * Tackled players must pass the ball, within one pace from the spot they were tackled, without delay.
 * The defence must not interfere with the first pass following a tackle.
 * Ball in touch the other side re-start with a pass from the point where the ball crossed the touchline
 * Turnover, penalty or other in-field re-start: the player restarting must tap the ball with foot or knee and may then walk or pass, on-side defenders may advance
 * Uncontested two-person scrums for knock-on/forward passes with 6 or more players a side

Additional Rules
Walking Rugby matches are friendly matches played by teams which can be of any gender (including mixed teams). This is an inclusive sport which welcomes players of all abilities and disabilities. https://www.wrugamelocker.wales/media/1537/wru3556-walking-rugby-rules.pdf These rules are drafted to allow flexibility when required. To accommodate the inclusive nature of the game, teams /festival organisers may agree on rule changes to suit local conditions and player abilities. The spirit and laws of the 15-a-side game will apply unless detailed below. • There will be no scrums, lineouts, mauls, and rucks. • Tackling, barging, hand-offs and kicking the ball are not allowed. • Players must not run or jog whilst the game is in play. MAJOR CHANGES FROM 15 A SIDE GAME • Matches are played with a size 4/5 ball. • 7 players on the pitch at a time per team. • Unlimited in-game substitutions can be made. A substituted player may return. • Matches are typically 8-12 minutes long and could include a halftime. • All teams should wear a sports kit or bib to identify players. If possible, watches and jewellery should not be worn. • For 7 a side matches, we advise a pitch size of about a quarter of a full-size rugby pitch. However, pitch size can be varied based on available space and player numbers. FESTIVAL LOGISTICS Veterans Touch Rugby Rules – 20223 • With the aim of the game to maximise accessibility, team captains and referees can agree on adjustments to apply for that match to take into account disability, age, or infirmity. • Starting play: • At the start and after a try, a free pass from the middle of the pitch. • If the ball goes into touch, restart with a throw from where the line crosses. • In all other instances, tap the ball with foot or knee and then walk or pass. • The ball must be passed backwards or transverse. • The defending team aim to touch the player with the ball. A touch should be two-handed from shoulders down to shorts, including arms. • If the attacking team has not scored within 6 touches - the ball is turned over to the opposition who restart where the 6th touch happened. • A player scores tries when at least 1 foot is placed on or after the try line. • If a player is touched whilst crossing the line, a try is scored provided, the line is reached or crossed by completing the step being made when touched. • A penalty try will be awarded if an infringement stops a try being scored. • If the ball goes to the ground without a knock-on the player nearest to the fallen ball may pick it up and continue play. The opposing team should not interfere with the pick-up.

The Game
The referee is the sole judge of fact and law. They are encouraged to try and make the games flow freely and can make allowances for the abilities and skills of players.

• Advantage should be used where possible. • Touches made by players infringing the rules can be discounted from the 6 touches rule, or the referee may reset the 6 touches and let the game flow or award a penalty. • Referees may also ignore infringements which do not materially affect play. • A neutral referee is preferred, and teams attending a festival may be requested to provide a person(s) who can act as a referee for matches involving other teams. • Touches should not be robust and consider the strengths/frailties of the player being touched. • Touched players may complete the pace they were in the process of making whilst touched and then must pass the ball within 3 seconds, without further movement. • If a player carrying the ball is touched and then travels more than this the referee should call play back to where the touch was. Play restarts with the same player in possession – touches are not reset. • The player making the touch must retire 1 pace, setting the offside line for their team. • If the defender making the touch interferes with the pass from the touched player, the attacking team have 6 fresh touches.

Touch Tackles
Veterans Touch Rugby Rules – 20225 • In the event of Offside, foul play, forward pass or knock the non-offending team restarts where the incident occurred and/or the 6-touch count is reset. • Foul play. Normal 15-a-side rules apply plus: • No running or Jogging at any time. • No pushing, barging, or dangerously making a touch. Including handoffs, walking straight into, or backing into an opposition player. • Tackler/Defender interfering with pass after a touch or not retreating. • Grabbing another player, trying to wrestle the ball away from them (by hitting the ball, snatching, or ripping). • The referee may ask that players who are deliberately and repeatedly infringing be substituted by their team. • The referee has the discretion to allow advantage and: • For minor infringements they could just exclude touches made by infringing players from the 6 touches count or deduct 1 from the existing touch count. • For more material infringements where the referee is still not stopping play the 6-touch count can be reset from where the advantage occurs.

Infringements
• When an Offside line is created all players in a team must try and retire into an onside position. • An Offside line is created as follows: • If a touch occurs the player making the touch must step back 1 metre and this sets the offside line for their team (or on their try line if closer). • At all restarts the attacking team have an offside line where the restart is; the The defending team have an offside line 2m nearer to their try line (or on their try line if closer). • If an offside player makes a touch it is excluded from the 6 touches count. If they also obstruct play the referee can reset play where the obstruction took place or play advantage by resetting the touch count. • Onside defenders may advance once the ball has been tapped or passed. • The Offside line lasts until the team with the ball has completed a pass or moved 2m with it. • In open play all players are onside

title: Walking Rugby/Rules


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User talk:Sharmilagnanakumarmalathi

Deletion of work
Hi, I have written a ton computerational thinking, and it has all been deleted, could you tell me if you delete this? CTuomi (discuss • contribs) 16:52, 26 January 2024 (UTC)

title: User talk:Sharmilagnanakumarmalathi


text: Category:Book:Walking Rugby

title: Category:Book:Walking Rugby


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Cookbook:Corned Beef

Corned beef is a variety of cured beef.

Characteristics
The production of corned beef starts with curing. Here, curing salts and spices such as peppercorn, juniper, coriander, and mustard are combined and applied to a tough cut of beef like brisket —this can be done as a dry cure or can be made into a brine for a wet cure. The beef is then cured for several days, which gives it a more complex, savory-sour flavor and preserves its pink color. Typically, the curing process is then followed by a long, slow braise to cook and tenderize the meat. It may also be smoked to make pastrami.

Selection and storage
Commercially, corned beef is available both "fresh" and canned. The canned version is typically chopped or ground and pressed into a block in the can—it is fully cooked and ready to use, and it has a very long shelf life. The "fresh" version is cured but not cooked, and it must be stored in the fridge before final preparation. Once cooked and/or opened, corned beef will last for a few days in the fridge.

Use
In the United States, corned beef is most commonly associated with Jewish and Irish cuisines, and it tends to be eaten in sandwiches or as part of corned beef hash. Canned corned beef is popular in cultures subjected to Western imperialism and military invasion, such as the Philippines and Hawaii.

title: Cookbook:Corned Beef


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A-Level Maths & Further Maths

Introduction
This book covers both A-Level Mathematics and Further Mathematics. It is separated by content and topics, rather than by different exam boards.

The A-Level Mathematics and Further Mathematics specifications were updated following reforms in the UK for GCE A-Level examinations. This new book is to cover all the changes in content and compile information from the previous wikibook that makes references to older specifications (specifically 2013 and earlier). The new specifications are linear and replaced module-based A-Levels. The first exams of the current specification were in 2017.

The majority of core content is set by the UK Department for Education and is assessed by exam boards, all of which add various amounts of additional content to exams. The current exam boards are AQA, Edexcel, OCR, OCR (MEI), CCEA, WJEC and CIE.

title: A-Level Maths & Further Maths


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User talk:Richard Nevell (WMUK)

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User talk:Beathebard

--ꠢꠣꠍꠘ ꠞꠣꠎꠣ (discuss • contribs) 20:00, 26 January 2024 (UTC)

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User talk:Zoetanya

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User talk:Brocoli168

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User talk:Il lupa

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title: User talk:Il lupa


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User talk:Starfishintheocean

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User talk:PBEdinburgh

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title: User talk:PBEdinburgh


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A-Level Maths & Further Maths/Algebraic Expressions

Fractions
Fractions are something that you should be comfortable using at this level, and should be second nature. Recall that $$\frac{a+b+c}{x} = \frac{a}{x} +\frac{b}{x} + \frac{c}{x} $$ is true, but in general $$\frac{x}{a+b} \neq \frac{x}{a} + \frac{x}{b} $$. It should also be reminded that the denominator cannot be zero.

Factorising Expressions
A factor is a number or variable that appears in multiple parts of an expression; it can be 'taken out' to help simplify an expression. For example, $$ax + ay $$ has a factor of $$a $$, so the expression can be simplified to $$a(x+y) $$.

Expanding Expressions
Expanding expressions basically reverses factorising. It is easy to make a mistake when expanding brackets, so care should be taken. A common example is $$(x + y)^2 = x^2 +y^2 + 2xy $$, where many students make the mistake of suggesting it is $$x^2 + y^2 $$. Another important one to remember is the difference of two squares: $$x^2 - y^2 = (x+y)(x-y) $$.

Indices
There are some basic rules to remember when working with indices:

$$a^1 = a $$

$$a^0 = 1 $$

$$a^m \cdot a^n = a^{m+n} $$

$$a^m / a^n = a^{m-n} $$

$$(a^m)^n = a^{m \cdot n} $$

$$a^{1/n} = \sqrt[n]{a} $$

$$a^{-m} = \frac{1}{a^m} $$

These will be revisited when looking at logarithms.

Surds
Surds are expressions involving square roots. Like indices, the basic rules are:

$$\sqrt{ab} = \sqrt a \sqrt b $$

$$\sqrt{\frac a b} = \frac{\sqrt a}{\sqrt b} $$

$$a = \sqrt{a^2} = \sqrt a \sqrt a $$

$$a-b = (\sqrt a + \sqrt b)(\sqrt a - \sqrt b) $$

Rationalising the Denominator
By definition, square roots are irrational. This makes them difficult to work with, especially when they are in the denominator of a fraction, when trying to simplify expressions. To help with this, we use the process of 'rationalising the denominator'. To do so, we multiply the numerator and denominator by the same number, as $$\frac a a = 1 $$, so we avoid changing the value of the fraction, but still change the numbers we are working with.

Example
To rationalise $$\frac{2 + \sqrt 3}{\sqrt 6} $$ the full working out would be

$$\frac{2 + \sqrt 3}{\sqrt 6} = \frac{2 + \sqrt 3}{\sqrt 6} \times \frac{\sqrt 6}{\sqrt 6} = \frac{2\sqrt 6 + \sqrt 3 \sqrt 6}{\sqrt 6 \sqrt 6} = \frac{2\sqrt 6 + 3 \sqrt 2}{6} $$.


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Open Scholarship Press Curated Volumes: Connection/Introduction

Digital Knowledge Commons, Scholarly Connection, and the Evolution of Open Scholarship
Graham Jensen (University of Victoria)

The enormous growth of digital knowledge commons and academic social networking sites in the last fifteen years or so has enabled millions of researchers to connect and share their work with others online. But during this same period, the remarkable transformation of digital infrastructure has also raised many questions about the nature and trajectory of scholarly communication and practice. In dialogue with Lucas Power about rapidly changing online platforms such as Facebook, Twitter, and YouTube, for example, literary and media studies critic Aarthi Vadde suggests that conversations around Web 2.0 and its maturation have occasionally fed into a growing tension between the meaning and value of “participation” versus “publication” (190). According to Vadde, this tension was exacerbated by the hyperbolic claims of Web 2.0 proponents, whom she accuses of having championed participation under the banner of social engagement and innovation even as they exploited it as a quantifiable metric or dataset that could be bought and sold. At the same time, publishing, too, inevitably took on new meanings as new venues for self-publication and user-generated content emerged. Vadde argues that this history can teach us not only about digital infrastructure and platforms in the present, but also about what participation and publication may look like in the future. Issuing a warning, she notes:

"There are absolutely elements of today's Internet culture that extend beyond the wildest dreams of the architects of Web 2.0, but its founding ethos of scalability and monetizable data remains unquestioned. The largest platforms could be called “webs unto themselves” or highly complex walled gardens that monitor every aspect of user activity with the intent of keeping users within their information ecology. [. . .]

Extremist groups and disinformation campaigns weaponize Web 2.0 principles and take advantage of the social web that has grown out of them. If scholars want to study where the social web is and where it is going, they can meet the moment by historicizing particular movements as well as particular platforms. (190)"

As Web 2.0 slowly and unevenly gives way to Web3 (or whatever comes next), the enclosure of digital spaces continues to transform the relationship between platforms and their users. In this way, the history of the tension between participation and publication, like the history of the internet itself, can be understood partially in terms of a shift from open to closed and commercialized forms of knowledge exchange.

But these histories are still being written. Against the currents of commercialization and weaponization, many individuals and collectives are interested in exploring how platforms can support both participation and publication—all while also remaining open; sharing information across seemingly discrete platforms or disciplinary domains; combating dis- and mis-information; and creating networks not for surveillance or the monetization of user activity and information, but for meaningful community building and communication. The authors in this volume do so “by historicizing particular movements as well as particular platforms” (to return to Vadde). In the process, their work builds on and feeds into growing bodies of research in the fields of scholarly communication, digital infrastructure studies, digital humanities, and many others.

My own research, as part of the Implementing New Knowledge Environments (INKE) Partnership, has benefited tremendously from these authors’ historical insights, and also their pragmatic attempts to parlay technological innovations and specific digital platforms or tools into positive, if gradual, changes to scholarly practice. Similar attempts are on display beyond the pages of this volume—including, for instance, in the Humanities Commons’ turn to a “fediverse” model of social networking as one possible response to the problem of commercial enclosure. Yet the concepts of interaction, connectivity, and openness themselves continue to be exploited rhetorically and commercially by social media giants such as Meta, which recently announced its own intentions to implement an open fediverse model (Woloshyn and Fraser 2023). Meta’s exuberance speaks both to the genuinely heartening potential of open infrastructure as well as its potential vulnerability to the very market forces and commercial entities that have always threatened to transform open, accessible spaces or resources into their opposite. While some critics may share the optimism of software developer and ActivityPub co-editor Evan Prodromou, who remarks of the fediverse that “it’s not about the platforms, it’s about the people” (qtd. in Woloshyn and Fraser), others might point out that any such claims must be considered against the historical record. For digital commons such as the internet, which is populated with platforms as well as people, that record remains a twinned record of innovation and exploitation, of inclusion and exclusion, of open commons and walled gardens.

❦

This Open Scholarship Press Connection collected volume includes reprinted critical interventions on the subject of digital knowledge commons or academic social networking sites and the forms of connection and open scholarship that they enable. Its ten full-length publications were previously annotated in the collection’s companion piece, the Open Scholarship Press Connection research scan / annotated bibliography, which is available on Wikibooks (https://en.wikibooks.org/wiki/Open_Scholarship_Press_Collections:_Connection) and PubPub (https://openscholarshippress.pubpub.org/open-scholarship-press-collections-connection). That annotated bibliography was developed by me (Graham Jensen, University of Victoria), Tyler Fontenot (Independent), Alan Colín-Arce (University of Victoria), Alyssa Arbuckle (University of Victoria), Vitor Yano (Concordia University), Anna Honcharova (European Students’ Forum), Caroline Winter (University of Victoria), and Ray Siemens (University of Victoria), with the INKE and ETCL Research Groups. Like that earlier research scan, which includes a more extensive introduction to and survey of digital knowledge commons and related intellectual issues, this collection takes its cue from the research questions that animate the INKE Partnership’s Connection cluster (https://inke.ca/activity-clusters/#connection). Although the curated selections gathered here represent a range of critical approaches and opinions, they share a keen interest in how scholars share and build communities around knowledge.

Those scholarly practices and communities have unsurprisingly shifted over time. Knowledge commons and open access, for instance, are contested concepts with complicated histories informed by modern science’s evolution over the past 400 years. As featured author Shawn Martin (2019) observes, these histories do not always map neatly onto present-day forms of scholarly research, communication, or publication. Still, he suggests that, in many ways, contemporary scholarly communication and knowledge production practices resemble those of earlier researchers, underscoring a persistent tension in today’s academic communities and knowledge commons between open access ideals and the practical, economic pressures that frequently prevent them from being realized. Of note, Martin’s brief account of the simultaneous application and commodification of scientific knowledge in the United States from the eighteenth century to the present usefully foreshadows one of the central concerns of the subsequent authors in this collected volume.

Offering a survey of the history and distinguishing features of popular academic social networking sites (ASNS), which are often discussed as a variety of digital knowledge commons, Katy Jordan (2019) also synthesizes scholarship in this still-nascent field. Jordan posits that there are two kinds of ASNS: “those which have been developed primarily to facilitate profile creation and connection (analogous to Facebook; examples include Academia.edu and ResearchGate), and those with a primary focus on posting and sharing academic-related content and have subsequently added social networking capabilities (such as Mendeley).” Curiously, this taxonomy carries traces of the distinction—as summarized by Vadde—between participation and publication. Furthermore, these categories are prefigured by the pre-digital networks of scholarly connection and communication referenced by Martin, as well as the sometimes open, sometimes commercialized and relatively closed forms of knowledge production with which academics continue to experiment in today’s digital world. But Jordan’s summary of scholarship on the use of modern ASNS indicates the extent to which digital platforms embody radically new approaches to age-old questions about access to information, the quantification of scholarly activity and outputs, interpersonal interactions, and so on. What is more, this study closes by highlighting the need for critics interested in ASNS to better understand how these networks are used and studied in non-Western, non-Anglophone contexts.

Looking to the future of digital knowledge commons, Martin Hensher, Katie Kish, Joshua Farley, Stephen Quilley, and Katharine Zywert (2020) use the COVID-19 pandemic to reflect on serious problems with how knowledge is currently created, circulated, protected, and monetized. As the authors explain, open knowledge commons seem to provide an answer to many of these problems, as well as related concerns regarding intellectual property, knowledge scarcity, and misinformation. Their intelligence briefing demonstrates the immediate relevance of such issues to the fields of health and medical sciences, information studies, information policy, and beyond. Indeed, their use of COVID-19 as a case study underscores that these issues are of topical but also global significance. Advocating for open, publicly funded research and knowledge commons, the authors implore researchers and the public alike to consider new ways of anticipating and responding to global crises moving forward.

Other contributions to this volume focus their critique on specific for-profit knowledge commons, with particular attention paid to Academia.edu. While this academic social networking site is immensely popular in certain disciplines, Katie Fortney and Justin Gonder (2015) analyze Academia.edu’s terms of use as part of a larger commentary on the differences between ASNS and institutional repositories—including how the financial interests of many academic social networking sites have led to unethical uses of member data. They also censure ASNS for adopting legal clauses that try to limit the control of users over their own research. Like Jordan’s survey, then, Fortney and Gonder’s essay clearly distinguishes between ASNS and institutional repositories, but it does so in order to draw attention to the ways that for-profit examples of the former have sometimes failed to live up to ethical standards and academic imperatives of the latter. Extending this critique, Brooke Erin Duffy and Jefferson D. Pooley (2017) take aim at Academia.edu’s Silicon Valley startup aesthetic and business model. They maintain that the popularity of this site, and others like it, stems from the intense pressures academics face to market themselves and their work. Discussing certain metrics, communication tactics, and features of the site’s design, they also explain how Academia.edu stands to gain from academic anxieties—and indeed, seems deliberately crafted to exploit them. In much the same vein, Gary Hall’s “What Does Academia.edu’s Success Mean for Open Access?” (2015) considers the fundamental differences between for-profit digital knowledge commons such as Academia.edu and institutional repositories, both ethically and in terms of their approaches to research data management. As Hall reminds readers, Academia.edu is beholden to its shareholders and is therefore tethered to an operational model that must ultimately prioritize profit over and above the goals of open scholarship, for example, or the long-term preservation of user-generated content. He critiques Academia.edu for profiting from aggregated research supplied freely by academics, but he also broadens his critique to include Google, Twitter, and other companies who sell and control user data in ways that are incommensurable with the Open Access movement and its guiding principles.

Taking a slightly different tack, Kathleen Fitzpatrick (2015) summarizes the problems with Academia.edu while also recommending possible alternatives. Echoing Hall’s concerns about Academia.edu’s exploitation of academic labour, she calls for her readers to consider adopting disciplinary repositories such as the Modern Language Association’s MLA Commons (now the Humanities Commons) rather than institutional ones. Since the original publication of Fitzpatrick’s contribution in 2015, many more researchers, librarians, and other information professionals are now asking—as Zoe Wake Hyde, the Humanities Commons’ community development manager, does in a May 2023 blog post—how they might “facilitate meaningful connections that lead to the creation of new knowledge to be shared openly.” This vision, which is very much at the heart of the current collection, is also reflected in Jon Saklofske’s “Digital Theoria, Poiesis, and Praxis: Activating Humanities Research and Communication through Open Social Scholarship Platform Design” (2016). Saklofske argues that scholarly communication has not continued to reinvent itself through, and alongside, new technological developments. Such developments, he suggests, have the potential to transform scholarly communication, including in ways that might establish open scholarship as a more common alternative to commercial and traditionally closed forms of publication. To this end, Saklofske proposes the widespread adoption of open research practices and gives several examples of the kinds of unconventional knowledge-creation and knowledge-sharing platforms he has in mind.

Providing another example of an open, not-for-profit platform that responds to the many issues catalogued by the other authors in this volume, Matthew Gold (2011) describes how BuddyPress—which is an open-source platform and suite of WordPress plug-ins—has served as a valuable tool for teaching and building community. While BuddyPress, like the Humanities Commons, leverages many of the features of popular social networking sites to facilitate easy connections between students and other academics, it deliberately attempts to distinguish itself from those commercial platforms. It does so by prioritizing openness, for instance, and by taking concrete steps to protect students, their data, and their metadata from being exploited, commodified, or shared inappropriately.

Similarly, in “Foundations for the Canadian Humanities and Social Sciences Commons: Exploring the Possibilities of Digital Research Communities” (2020), Caroline Winter, Tyler Fontenot, Luis Meneses, Alyssa Arbuckle, Ray Siemens, and the ETCL and INKE Research Groups introduce the Canadian Humanities and Social Sciences (HSS) Commons as an open, online space for academics, research partners and stakeholders, students, and interested members of the public. After sketching out a history and theoretical foundation for the concept of the commons, they discuss how digital knowledge commons such as the Canadian HSS Commons—which includes a wide-ranging suite of tools for members both in Canada and beyond to build community and freely publish, share, and connect over research—can transform scholarly communication through open scholarship. As such, the Canadian HSS Commons constitutes another researcher-led response to the problem of enclosure outlined above.

As digital knowledge commons continue to proliferate, they will continue to transform scholarly participation and publication, inspiring and embodying novel forms of each. But the evolution of digital knowledge commons—and digital tools and technology more generally—must also be accompanied by continued critical consideration of what creating and maintaining these complex and diverse systems will involve, and mean, for future communities of researchers or creators and consumers of knowledge. This responsibility is and necessarily will be a shared one. As Joseph North notes in “Criticism as a Practice of the Commons” (2023), “as soon as you describe something as a commons, you are inclined to pose questions like, ‘Who has access to this, and who controls that access?’—and you are inclined to want to answer both questions by nominating groups, rather than individuals” (4). While the authors in this collected volume address such questions of access, enclosure, and governance in various ways, and from a variety of disciplinary perspectives, their responses to the problems endemic in our current scholarly ecosystem suggest to me that the social, collective nature of commons is paradoxically both the source of many such problems and the reason one can nevertheless hold out hope for their resolution. As emphatically social spaces built by and for scholarly communities of practice, open digital knowledge commons such as the Humanities Commons and the Canadian HSS Commons can play an important role in supporting the continued success and growth of these communities. By prioritizing open scholarship over profit and connection over competition, it is our hope that digital knowledge commons of this kind can positively transform scholarly networks not only in the ways detailed in this volume, but also in ways we have yet to imagine.

Works Cited & Original Citations
Duffy, Brooke Erin, and Jefferson D. Pooley. 2017. “‘Facebook for Academics’: The Convergence of Self-Branding and Social Media Logic on Academia.edu.” Social Media + Society 3 (1). https://doi.org/10.1177/2056305117696523

Fitzpatrick, Kathleen. 2015. “Academia, Not Edu.” ''Really, We’re Helping To Build This. . . Business: The Academia.edu Files''. Liquid Books. http://liquidbooks.pbworks.com/w/page/106236504/The%20Academia_edu%20Files

Fortney, Katie, and Justin Gonder. 2015. “A Social Networking Site Is Not an Open Access Repository.” ''Really, We’re Helping To Build This. . . Business: The Academia.edu Files''. Liquid Books. http://liquidbooks.pbworks.com/w/page/106236504/The%20Academia_edu%20Files

Gold, Matthew. 2011. “Beyond Friending: BuddyPress and the Social, Networked, Open-Source Classroom.” CUNY Academic Works. Publications and Research, CUNY Graduate Center. https://academicworks.cuny.edu/gc_pubs/291

Hall, Gary. 2015. “What Does Academia.edu’s Success Mean for Open Access?” ''Really, We’re Helping To Build This. . . Business: The Academia.edu Files''. Liquid Books. http://liquidbooks.pbworks.com/w/page/106422609/What%20does%20Academia_edu%E2%80%99s%20success%20mean%20for%20Open%20Access.

Hensher, Martin, Katie Kish, Joshua Farley, Stephen Quilley, and Katharine Zywert. 2020. “Open Knowledge Commons versus Privatized Gain in a Fractured Information Ecology: Lessons from COVID-19 for the Future of Sustainability.” Global Sustainability 3. https://doi.org/10.1017/sus.2020.21

Hyde, Zoe Wake. 2023. “The Web We Want.” Platypus: The Blog of the Humanities Commons Team, May 30, 2023. https://team.hcommons.org/2023/05/30/the-web-we-want/

Jensen, Graham. 2022. “Creating Connections in and through Knowledge Commons.” Open Scholarship Press Collections: Connection. https://openscholarshippress.pubpub.org/pub/uo36o9ut/release/3?readingCollection=f6d1065d

Jensen, Graham, Alyssa Arbuckle, Caroline Winter, Talya Jesperson, Tyler Fontenot, Ray Siemens, ETCL Research Group, and INKE Research Group. 2022. “Fostering Digital Communities of Care: Safety, Security, and Trust in the Canadian Humanities and Social Sciences Commons.” IDEAH, June. https://doi.org/10.21428/f1f23564.ed75625f

Jesperson, Talya, Graham Jensen, Caroline Winter, Alyssa Arbuckle, and Ray Siemens, with the INKE Research Group. 2022. “Open, Collaborative Commons: Web3, Blockchain, and Next Steps for the Canadian Humanities and Social Sciences Commons.” ''Pop! Public. Open. Participatory'' 4 (October). https://popjournal.ca/issue04/jesperson

Jordan, Katy. 2019. “From Social Networks to Publishing Platforms: A Review of the History and Scholarship of Academic Social Network Sites.” Frontiers in Digital Humanities 6. https://doi.org/10.3389/fdigh.2019.00005

Martin, Shawn. 2019. “Historicizing the Knowledge Commons: Open Access, Technical Knowledge, and the Industrial Application of Science.” KULA: Knowledge Creation, Dissemination, and Preservation Studies 3 (February): 23. https://doi.org/10.5334/kula.16

North, Joseph. 2023. “Criticism as a Practice of the Commons.” PMLA 138 (1): 151–57. https://doi.org/10.1632/S0030812922000992

Power, Lucas, and Aarthi Vadde. 2022. “Publisher 2.0.” PMLA 137 (1): 188–90. https://doi.org/10.1632/S003081292100081X

Saklofske, Jon, and INKE Research Group. 2016. “Digital Theoria, Poiesis, and Praxis: Activating Humanities Research and Communication through Open Social Scholarship Platform Design.” Scholarly and Research Communication 7 (2/3). http://src-online.ca/index.php/src/article/view/252

Winter, Caroline, Tyler Fontenot, Luis Meneses, Alyssa Arbuckle, Ray Siemens, and the ETCL and INKE Research Groups. 2020. “Foundations for the Canadian Humanities and Social Sciences Commons: Exploring the Possibilities of Digital Research Communities.” ''Pop! Public. Open. Participatory'' 2 (October). https://popjournal.ca/issue02/winter

Woloshyn, Roxanna, and Ashley Fraser. 2023. “What Is the Fediverse and Why Does Threads Want to Join?” CBC, July 19, 2023. https://www.cbc.ca/news/business/fediverse-explainer-1.6905837