Freedom of misinformation – LIANZA 2023

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Rob Cruickshank (LIANZA Standing Committee panel chair)
Leslie Weir (Librarian and Archivist of Canada)
Māia Abraham (Christchurch City Libraries)
Distinguished Professor Steven Ratuva (University of Canterbury)
Associate Professor Spencer Lilley (Victoria University of Wellington)

> What’s the extent of the problem of misinformation in our society today and the effect on Indigenous people?
Leslie: In Canada, 150000 children attended “Indian Residential Schools” – many never returned home and of these the death of many was never recorded. Misinformation of the time shut down people trying to get the story out and erased the history. Now reckoning with this history and need to work to make sure it’s recognised.
Māia: In Aotearoa we’ve been dealing with misinformation around Te Tiriti o Waitangi. It’s come in through the history of Western education in New Zealand as Hana O’Regan discussed (in an earlier keynote: she noted that eg in the 1930s the ministry of education overrode teachers’ recommendations and kept Māori language out of the curriculum on the grounds that it would actually be good for them to lose it).
Steven: The role of politics and the media. Example of the “Voice” referendum in Australia, and of dicussion of “co-governance” recently in New Zealand. All draws from pre-existing prejudices and misinformation about the hierarchy of humanity. Knowledge is not neutral – it has to do with power. Indexing can be used to reinforce prejudiced worldviews. Advertising is another forum where very little is truthful – and lots of fast food ads are targeted towards Māori and Pasifika using stereotypes – maybe not consciously/intentionally but it’s embedded in the subconscious.
Spencer: Looking at critical information literacy skills. Eg Elsdon Best taking information from Tuhoe informants, filtering it through a Western lens, and applying it as if it were something Māori believed as a whole. Expecting all Māori to think the same, have the same tikanga etc is its own kind of misinformation. A lot of misinformation issues today are around trust.

> What can we of librarians do about this given we have a responsibility to provide access to information?
Leslie: We hold all the original treaties, records of the residential schools etc. Currently tend to work nation to nation considering the question of data sovereignty as (like iwi and hapū in Aotearoa) there’s no one size fits all.
Māia: It’s a personal responsibility, thinking about our responsibility as librarians. Consider who has the rights to the information. Be intentional about who we’re hiring/training to work with the collections. Think about your organisation history. Libraries ultimately are a Western way of collecting and organising information though this doesn’t mean Māori information can’t exist there.
Steven: ‘Harm’ can mean different things to different people. Sometimes get students to research something they disagree with. Commodification of knowledge – publication as a way to move up the academic ladder. Elsevier profits $3.3billion off of researcher work and then we have to pay to access it again. Ethics gets thrown out the window by commercialisation.
Spencer: Lots of work going on in the open access space. But need to ensure that metadata for publications beats the algorithms. Need to get OA content ranking higher than content from the traditional systems. Need people to get content from multiple sources and do their own thinking instead of going to an AI generator.
Steven: Scopus algorithms aren’t friendly to Indigenous knowledge – they keep out Indigenous journals, almost seems intentionals. Researchers forced to get their metrics up in order to be promoted but hard for Indigenous researchers to do this when their journals aren’t indexed.

> What can libraries do practically?
Leslie: We need to contextualise material – work with communities to identify advisories/context that needs to go on material. Especially if material may contain traumatic content. May need support services.
Māia: No one size fits all. Work with the people around you to come up with a solution – don’t wait for a solution to fall into your lap – and to implement it.
Steven: Can’t start censoring books (different people would pick different books to ban, and there’d be an outcry). But could have a team exploring which books would create the most harm – and identify rather than burn them.
Spencer: Comes back to education – of people working in our institutions so we’re aware of our own collections, and be aware to use skills to educate others. Be allies of Māori and Pasifika staff and communities. Libraries have always been a strong advocate of freedom of information, need to drive this home in our collection development policies.

Enhancing library instruction through peer review – LIANZA 2023

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Elizabeth Sturrock & Lyndall Holstein – Massey University
Created a new class “introduction to open access” and set it up so it’d be on the professional development calendar. So they wanted it to be “right” the first time – so wanted feedback from peers to make sure the teaching was hitting the mark: did it get the idea across clearly, have good pedagogy, content pitched at the right level. It was also a chance to collaborate with colleagues!
Did two real-time presentations across all campuses, presenting as they would in reality, and asking for all possible feedback. (Attendees were library colleagues, including student assistants new to the topic, and some external people.) Got feedback straight after the session, via anonymous forms, in tearoom conversations etc. Practiced active listening (no arguing!)
Collected and categorised feedback into categories. Some about the scope; some advised on tech options; too much reading of words on slides; lots of jargon. Implemented feedback with edits to slides, changing presentation style, incorporating more activities.
Presented again with changes and took more feedback but then it was minor tweaks only.
Finally presented the class for real. 20 attendees mostly associate professors, 100% attendance! Got really positive feedback from participants. Have now done it 7 times in total and also developed an offering for PhDs which was also peer reviewed.

The process worked well – the class was ready to roll out on time. Were happy with willingness of colleagues to peer review work – and with their own reactions to the work being critiqued. Helped leading the way for others to take on feedback about their teaching too – normalising peer review in the culture.
Could have been useful to get user feedback before it was presented officially. It was also difficult to get colleagues to move past general ‘It was great!’ feedback.
Want to extend the approach to all general teaching including Endnote classes, researcher development library workshops – and this session. Want to review teaching on a more regular basis, rather than just ad hoc tweaks.

Takeaways

  • Get in the headspace for critique – stay positive and listen – you don’t need to respond and justify yourself
  • Remember your goal to produce a digestible workshop
  • Incorporate what works – you don’t have to follow all the advice if you have reasons to disagree after reflecting on it
  • Collect feedback via multiple methods – some people give immediate feedback, others think on it and feedback later – some do both!

Designing future blended libraries – LIANZA 2023

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Patricia Velasquez
Libraries have redesigned/innovated a lot to meet user needs.
Looked at concepts of physical space; digital space; blended space. Benyon 2012 described blended space – eg in the library context:

  • ontology – the objects users can use
  • topology – how the objects complement each other
  • volatility – how flexible is the face
  • agency – the people in the library space

Cunningham&Tabur 2012 described learning space attributes analogously to Maslow’s hierarchy of needs:

  • comfort and image <- apex
  • sociabiity
  • uses and activities
  • access and linkages <- base

Research to help libraries understand experience of users. Did document analysis, individual interviews, observation, focus group discussions.
Students’ challenges:

  • wifi strength, consistency – especially with online classes
  • library promotion – may not find out about library services until near graduation!
  • signage – either not enough or too much
  • lack of self-service guide
  • lack of BYOD support, power points
  • inconsistent policies etc

Students’ preferences

  • flexibility eg table height, opening windows
  • self-service – want to be able do it themselves — but otoh
  • human interaction. (Different groups have different preferences! We need to be careful when we make changes…)
  • variety of resources – print, electronic, etc
  • ease of use
  • availability (and accessibility)

Talking with them: students see the physical space as a transient space where people come and go. See library as a repository of knowledge where it can be found/access and learning happens. Haptic experience – want to be close to books, smell them – this is motivating.
They talk about the digital space – importance of online browsing and searching (but need to think about ease of use). Personalisation stil relevant. Want user-friendly technologies.
They want increased use of physical and digital elements of the library. Improve BYOD support. Have identified the disconnect between physical and digital elements – eg look for a book online but when they come to campus and can’t find it.
Students use the library (collection, building, services) if they perceive it to be helpful). We need to make the transition between physical and digital more seamless.

Transdisciplinary design of a future library – LIANZA 2023

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Dawn Carlisle
Backdrop of project is merger of polytechs into Te Pūkenga. Other challenges: honouring obligations under Te Tiriti; ever-changing nature of technology; Covid-19.
Transdisciplinary research: methodology that sees a subject and issue from all angles and disciplines. Allows for collective understanding from the community involved in the subject and issue. (Compared to interdisciplinary research which might ‘only’ come from the point of view of a couple of disciplines.)
Explored what a future academic library service could look like in Aotearoa bearing in mind these challenges, and looking at it from all angles. Including library as space, librarians as teachers, library kaimahi, decolonization and Te Tiriti, “industry 4.0 technology” (robots, AI, AR, etc).
5 surveys with 62 participants. Interviews with library professionals; a library managers forum; a Te Tiriti workshop.
Analysed using Constructivist Grounded Theory which is a reflective iterative approach of working with data from the various interviews etc.
Insights:

  • We need equity and understanding – move away from Eurocentric model; increase Indigenous staff; improve understanding of Indigenous knowledge; be comforting, welcoming spaces
  • Centralisation is beneficial – but can’t lose individuality. Need to know people and histories of local land
  • Technology – implemented into our work
  • Treaty partnerships – work within mana whenua in our communities, keep communication open
  • Improving access – currently each ITP has to negotiate its own access to databases – Te Pukenga merger is an opportunity to change this.

Lots of future avenues for exploration.
As a result of the work developed featured library guides around Aotearoa history; mātauranga Māori; Pacific knowledge. resources/services for Wintec researchers; and Equity&Inclusion.

Library collection evaluation – LIANZA 2023

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Ivy Guo and James Bagshaw, Victoria University of Wellington
James evaluates collections by looking at usage stats. Mostly online as 97% of collection budget is for electronic resources.
Combine everything, gather usage statistics, determine a cost-benefit, and seek feedback – this is a cycle. They mostly use COUNTER reports where available. Can look at usage on the book/journal level, and also on the article/chapter level. Database reports include multimedia stats (where the title-level ones don’t). “Investigations” are where someone’s looked at eg the metadata, abstract, preview. The “request” is for full-text view/download (or in the case of multimedia, where the item is played for at least 10 seconds. Lots of info at the COUNTER website.
Good practice – standardised reports, good records management, and combine data into one place as much as possible. Excel does provide a lot of power to do this eg with pivot tables and formulae. (“It’s not my best friend but I’m on quite good terms with it.”)
How do we evaluate Open Access? 80% of OA usage is currently not tracked (according to COUNTER). “Global Item Report” might help track this so can measure not just institution usage but also wider “world” usage.

Ivy points out “there is such thing as too much data”. How do we read it all and find the useful thread in it to tell the story. You need to have your questions in mind first then look at the data. It also needs to be presented in a meaningful way to stakeholders.
In decision-making: “Be bold” which doesn’t mean reckless, but we’ve got the skills, we’ve done the consultation, so “trust the data and trust the process”.

James notes data often presents more questions than answers. Sometimes you see usage stats are low and discover your authentication system isn’t set up correctly!

Engaging academics and researchers over coffee – LIANZA 2023

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Elizabeth Sturrock and Stephanie Cook, Massey University
Have been doing library outreach by offering weekly dropins outside of the library space. Based on the Auckland campus of Massey – they’re subject librarians focusing on the College of Health subjects. All academics and PhD students are in the same place (and master’s students often visit) so it’s easy to target them there.
Wanted to spread the message about what they do and how they can help, and foster relationships and build trust. Wanted to remove barriers by going to them. The initial idea for drop-ins was at end of 2019. Had to park the idea for 2020 but in 2021 decided to just do it. Some success though hampered by continued lockdowns, then restarted in 2022 and committed to nearly every week in 2023.
Asked for permission to come to the tearoom for an hour each week – college administrator was happy to facilitate. Picked a time they hoped would have most people. Sent out reminders via the administrator each week though no longer need to do this. Both attend to show commitment, and useful if more than one person wants to talk. Take their laptops (can work when quiet, or use it to look things up. Wear badges, put a sign on the back of the laptop, and grab a hot chocolate to wait facing outwards so they’re visible but not in the way.
Since doing it regularly, starting to see more people. Usual queries eg Endnote but also CV writing and other non-library questions where they can redirect to another service team; or sometimes just chatting. Keep notes in an Excel spreadsheet.
Good successes especially over the last year. Eg an academic they hadn’t seen much before came to talk and said “While you’re here…” – turned into a large conversation, some work they could do for him for a service he didn’t know about, which he then passed on to other colleagues. Academics referring PhD students to them.
The virtual drop-ins were a complete flop – no-one came at all.
Benefits for researchers:

  • access help at point of need
  • customised support
  • regularity – so people become familiar with them, less scary to approach them
  • informal environment – so they don’t have to have a really well thought-out question, can just chat

Benefits for library staff:

  • no preparation
  • get to know people in their own space – on a more ‘personal’ level
  • spreads the word about what they do

Challenges:

  • Finding a suitable time – nothing suits everyone
  • Maintaining weekly attendance
  • Uncertainty – maybe no-one will turn up. But at least can wave to people. Haven’t had a week with nobody for a long time – and sometimes even have a queue.

Good feedback from staff. Especially hear “While you’re here…” very frequently. Even if they don’t have a question they like the library presence in case.
Suggestions:

  • Pick the right location and time – as few barriers as possible so staff don’t have to book, search, login, etc
  • Visibility in the space – so they can see you and can see others engaging with you. (Another attempt in another department were consigned to a meeting room and rarely got people coming in.)
  • Persistence, regularity
  • Face-to-face

Looking at more targeted drop-ins to focus on eg ORCiD signup. Want to experiment with other days/times.

Rangi Mātāmua’s keynote – LIANZA 2023

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Professor Rangi Mātāmua (professor of Mātauranga Māori at Massey University) started talking about growing up with his mother as a Māori librarian and the family garage being so full of books his father couldn’t park the car there – but never about finding the book, rather about connecting people with information.

His background is cultural astronomy – has travelled around the world including Greenwich – the knowledge base coming from Te Kokau. Te Kokau was resident expert in Māori astronomy and the key informant in Elsdon Best’s book “The astronomical knowledge of the Māori” though not named as such. He wrote a 400-page manuscript. 987 individual stars – what it is, when it rises/sent, what it means. 103 constellations (some change depending on the season). A curriculum for how to teach astronomy. Manuscript was passed to his son, who handed it to his grandson and so on down to Rangi Mātāmua (where it’s currently in a wardrobe: he was told not to let the manuscript go, but to share the knowledge).

Lots of recent books coming out:

  • Living by the moon
  • Ngā mata o te marama
  • The maramataka: the many faces of the moon
  • Traditional Ecological knowledge of the maramataka

Prof Mātāmua focusing on astronomy’s relationship with time:

  • Sun = season. (These days we’re severed from this into an industrial system where the clock rules everything.) Where it’s rising in the morning shows the season
  • Star = month or activity. Stars in the morning sky change and indicate what activities you should be doing
  • Moon = day.

Triangulate these three things just like a clock with its hour/minute/second hand. Eg Matariki shifts depending on the moon (just like Easter). When the sun rises in the northeast it’s winter; when the stars indicate it’s Pipiri; and the moon is in the Tangaroa lunar phase –> then you can look for Matariki. (It might have been visible earlier, but that was the incorrect period to celebrate it.)
Mihi to the libraries who’ve taken a lead in celebrating Matariki.
“If you want to know what’s important to a society, look at what it celebrates.”
What is Mātauranga Māori?
It’s a modern term, less than 20 years old. “Mātauranga” is a response to Western knowledge systems. (Traditionally more likely to see kōrero or wānanga.) “Māori” of course just means “normal” (eg waimāori = freshwater). Māori knowledge systems; can’t exist in isolation from practice. “The practice underpins the knowledge and the knowledge affirms the practice.” Culture lives by being practised – not set in a glass case in a museum.
What is librarians’ role?
“You are the aho between the knowledge and the people.”
This year 51% of NZers did something to celebrate Matariki – especially at libraries and marae. People will continue to seek a deeper connection to our environment, and to Mātauranga Māori about it. This has to be done in collaboration with Māori – communities still hold knowledge bases that haven’t been shared.
Mātauranga Māori librarians are the go-to for everything Māori – this can be unfair – but this work is extremely influential.

State of Open Data 2019 #FigshareFestNZ

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State of Open Data 2019 report
Dr Mark Hahnel, Figshare

EU reckons it could save 10.2billion Euros a year using FAIR data. In the US the OPEN Government Data Act has been signed. NIH has said it requires everyone to make all their data available – but where are they going to put it?

FAIR – at least start with F and don’t name it “dataset.xlsx” because that’s hardly findable.

Figshare/Zenodo/Dryad – increasing uptake over time 20-30% year on year. Effects of EPSRC mandate in UK, NSFC mandate in China are significant. NZ is actually following the same trend even without mandates – global culture seems to be having an effect.

arXiv:1907.02565 found linking paper to dataset associated with 25% increase in citations

Annual survey – 8500 responses (three times as many as last few times)

  • 74.5% responses were extremely/somewhat likely to use other people’s data
  • 2/3 say funders should mandate data sharing, and 2/3 say that funders should withhold funding if people don’t
  • 66.4% think they don’t get enough credit for datasets – they want full citation, co-authorship (of paper based on their data – technically against norms but many do get it), consideration in job reviews, financial reward
  • Awareness of FAIR – slightly up but still <20% familiar, <30% heard of them

South African data repository (for compliance with a funder there)

NZ Research Information System #FigshareFestNZ

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NZ Research Information System (NZRIS) update.
Chris Dangerfield, MBIE

Concept model covering goal/purpose, resources, requests for resources, asset pools (eg funds), awards, projects, activities, people, teams, proposals, organisations…

Data model divided into two sides “asset pool managers” (funders) and “research, science and innovation managers” (eg unis, CRIs)

Implementation Phase 1 – plan to release in March with publically available historic data (from 2009 to present), with mostly mandatory data resulting from HRC proposals, Marsden Fund, Endeavour Fund, Sustainable Farming Fund, Partnerships, etc.

Phase 2 – bringing on more funding organisations and bringing in optional data

Review of phase 1 – data sovereignty, privacy, engaging with Māori stakeholders, creating engaging visualisations, improving data quality

Phase 3 – bring on unis, CRIs, etc in 2021-2022 – looking at projects, outputs (including datasets)

More information

Preparing the healthcare workforce #FigshareFestNZ

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Preparing the healthcare workforce to deliver the digital future – the good, the bad and
the ugly.
Dr Ehsan Vaghefi

Lots of lessons learned through commercialisation involving AI.

The Good

  • Great for science – IBM’s Watson Oncology can provide evidence-based treatment options, generate notes and reports, etc: the oncologist then audits this. Enables the hospital to increase capacity as AI is doing heavy lifting. Would it replace radiologists? Some yes; but other jobs have been created to work with the AI.
    • linking diseases to different genetic profiles
    • predicting possible treatments/vaccines for testing
    • AI-assisted cardiac imaging system
  • Gift of time – clinicians will have more time to focus on interacting with patients
  • (Good reads: “The patient will see you now”
  • Ophthalmology/optometry relying heavily on pattern recognition eg AI often more accurate detecting cataracts; can match accuracy detecting glaucoma (which you otherwise don’t know you have until too late); can match accuracy detecting diabetic screening

The Bad

  • Implementation – customer request, design, documentation, customer actual needs often all very different!
    • Eg one example where they provided more information to clinicians it slowed them down and made them worse. Clinicians are scared of AI so start double-guessing themselves. They do get faster using it with AI with more practice – but never reach their unassisted screening rates! Similar study in Thailand – when gathering data, clinicians only passed on the good data that they were confident about. So when AI tried to deal with ambiguous situations it didn’t cope.

The Ugly

  • Deepmind Health got more than 1million anonymised eye scans with related medical records – then sold themselves to Google. (In 2017 UK ruled that the NHS had broken the law in providing medical records.) Microsoft partnering with Prasad Eye Institute in India. IBM acquiring Merge Healthcare and IBM Watson analysing glaucoma images for deep learning. Streams medical diagnosis app to help you self-manage your health – and provides the results to hospital and your insurance company…..  Zorgprisma Publiek “pre-clinical decision-maker” helps “avoid unnecessary hospitalizations” – in practice the hospital can see in advance that you’ll be a costly patient and not admit you.
  • Re-identification – based on a single photo you can guess so much about a person you can start to work out who the person is.
  • AI bias – racism – based on incomplete datasets. Eg police using AI to assign risk factor based on risk background and face but because it’s got lots of racially biased data, it produces racially-biased risk factors. Eg a health-care algorithm where only 17.7% of patients receiving extra care were black (should have been 46.5%). Vital to be very careful about data collection – who’s contributing and not contributing – and invest more in diversifying the AI field itself.

Is ethical AI an oxymoron? Need to work out data ownership, governance, custodianship, security, impact on future.

Five pillars ethical AI

  • Transparency (informed consent etc)
  • Justice and faireness (make sure you’re not missing parts of the community)
  • Non-maleficence
  • Responsibility
  • Privacy

Is ethical AI a bargain/contract? A bargain struck between data sources and data users. Science needs data so it must be shared – but what benefit does the data source receive? Next evolution of big data in healthcare is “learning health systems” so instead of just holding your information the system can learn about you and give you better treatment.

Is privacy always beneficial? Sometimes sharing the data with an AI lets you get a better treatment plan.

A roadmap: “First do no harm”. Choose the right problem, not going fishing for data and make sure when gathering data the population understands everything about the research