Maggie Appleton talks with us about her work at Elicit, working with large and small language models, how humans vet the responses from AI, the discussion around the Soggoth meme in AI, using Discord as UI, what to do if your boss wants AI in your app, and why does she call her blog a digital garden?

ZeroFifty Mediaworks, set up by three ad veterans, wants to bring in Bandra vibes into the agency model

Montreal : National Film Board of Canada, 2012

The AJR Eurocentric framework falls short of representing the Global South, oversimplifies history and ignores diverse development paths

New York, NY : Routledge, 2016.

New York : Routledge, 2020

New York, NY : Routledge/Taylor & Francis Group, 2016

Full Schedule
Proceedings

Best quote: Librarians are like Mr. Paperclip from MS Office - we pop up when you least expect it and try to offer to you help...

This conference focused on the science library's role in supporting e-science and integrating into research collaborations and science departments. There was a mixture of speakers: government, library and institute directors, and a few librarians. The presentations were a mixture of big picture descriptions and some concrete examples. I felt like there wasn't as much hard solutions that we could take back to the library and implement, but perhaps just educating the library community on how radically different e-science is changing the research landscape is the necessary first step.

I've included the highlights from my session notes below (let me know if you'd like the see my full notes in gory detail). Check out the proceedings link above for powerpoint and document files for most of the speakers.

As a side note, our poster about GatorScholar was well-received with many people already aware of the project from either Val's USAIN presentations, the SLA poster, or from hearing about Cornell's project. Medha Devare was one of the panel reactors and she mentioned our collaboration in her presentation. Most of the poster visitors seemed very interested in starting their own version and perhaps at some point we'll have a network of databases.

Thursday

E-Science: Trends, Transformations & Responses

Convener and Moderator: Wendy Lougee, University of Minnesota
Speaker: Chris Greer, Director, National Coordination Office

2. A Case Study in E-Science: Building Ecological Informatics Solutions for Multi-Decadal Research

William Michener, Research Professor (Biology) and Associate Director, Long-Term Ecological Research Network Office, University of New Mexico


3. Rick Luce, Vice Provost and Director of University Libraries, Emory University Libraries

"Making a Quantum Leap to eResearch Support: a new world of opportunities and challenges for research libraries"


Wendy Lougee

Pitfalls: not to fall back on traditional roles, currently we don't respond to multi-institutional collaborations, our boundaries stop with the institution

We need to understand scientists' workflows, need to identify strategies for embedding librarians into project teams. We need to think about core expertise of librarians, reimaging roles of librarians

What do we do to build this collaborative action? We need to think outside the box.

Data Curation: Issues and Challenges

Convener and Moderator: James Mullins, Dean of Libraries, Purdue University

• Liz Lyon, Director, UKOLN

Transition or Transform? Repositiioning the Library for the Petabyte Era

How can libraries work with science (in a very general sense)?

1. Transition or Transform? Need to become embedded and integrated into team science. Many different models of engagement

Geosciences pilot where the library worked with the Geological department to curate their datasets (Edinborough):
Found: Time needed is longer than anticipated, inventory doesn't have to be comprehensive, little documentation exists
Outcomes: positive, requirement for researcher and auditor training, need to develop a data policy

2. Lots of opportunities of action: leadership by senior managers, faculty coordination, advocacy & tranining, data documentation best practices

People and Skills: there are not enough specialised data librarians. In UK 5 data librarians. Need to bring diverse communities together - facilitate cooperation between organizations and individuals.

Open science: new range of areas where results are being put onto the web (GalaxyZoo eg.) Librarians need to be aware of implications.

3. Need multidisciplinary teams and people in library, huge skill shortage, need to find core data skills and integrate it into the LIS curriculum. Recruit different people to the LIS team, rebrand the LIS career. Go from librarianship to Informatics.

• Fran Berman, Director of the San Diego Supercomputer Center, UC San Diego, and Co-chair Blue Ribbon Task Force on Sustainable Digital Preservation and Access

"Research and Data"

Researchers are detectives, shows different major questions (SAF, Brown Dwarfs, bridge stress, Income dynamics over 40 years, Disease spread-Protein Data Bank) - key collections all over.

CI Support: all these issues are crucial. researchers want a easy to use set of tools to make the most of their data.

She finds different preservation profiles: timescale, datascale, well-tended to poor, level of policy restrictions, planned vs. ad hoc approach

Researchers focused on new projects, customization of solutions to problems, collaboration

Researchers need help: developing management, preservation and use environments, proper curation and annotation, navigating policy, regulation, IP, sustainability

Questions about preservation: what should we save and who should pay for it? Just saving everything isn't an option. 2007 was the crossover year - digital data exceeded the amount of available storage. What do we want to save? Who is we?
Society: official and historically valuable data, Fed agency or inst normally takes part.
Research community: PDB, NVO.
Me: medical record, financial data, digital photos - real commercial market for preservation solutions.

What do we have to save?
private sector: HIPAA, Sarbanes-Oxley,
OMB regulations for fed funded research data (3 years, not always easy to do).

Economics: many costs associated with preservation. Maintenance upkeep, software, utilities, space, networking, security, etc.

UCSD forged partnership with library. Trying to create a preservation grid with formal policies, nationwide grid with other institutions.

Panel Responders:

• Sayeed Choudhury, Associate Dean of University Libraries and Hodson Director of the Digital Research and Curation Center, Johns Hopkins University

Data Curation Issues and Challenges:

It makes sense to help scientists deal with public and higher levels of data, not the raw data.

Considerations: need to work within their systems, consider gateways for systems as part of infrastructure development (think about railroad gauge), focus on both human and tech components of infrastructure, human interoperability is more difficult than tech interoperability, trust is key!

Questions: What about the cloud or the crowd? Can Flickr help us with data curation? What are the fundamental differences between data and collections? Human readable vs. machine readable? How do we transfer principles into new practices? What are we trying to sustain? Data? Scholarship? Our organizations?


Supporting Virtual Orgs

• Thomas A. Finholt, Director, Collaboratory for Research on Electronic Work (CREW) and Research Professor & Associate Dean for Research and Innovation, School of Information, University of Michigan

Changing nature of geographically-distributed collaboration:

history: transition in terms of distributed work. Much of what came before (collaboratory, video conf) had a precedent but new emerging has no precedent (crowdsourcing, VO's), no traditional context leaves us a bit adrift.

Lesson 1: anticipate cultural differences.
Domain scientists: characteristics: power distance (bias toward seniority, hierarchical), individualist(solo PI, individual genius), masculine(adversial and competitive), uncertainty avoidance
CI developers: power distance (bias toward talent, egalitarian), collectivist(project model), masculine, embrace risk

Lesson 2: plan for first contact.

It can be tough to recognize successful innovations: first efforts are often awkward hybrids



Crowdsourcing: idea that we send out challenges and solutions come to us (ex. Innocentive website, Games with a Purpose). We don't know who is going to do the work, effort is contributed voluntarily -> incentives are important to motivate work

Delegation of organizational work: people can count on organizations to do some of the basic policy work. Much attention has focused on technology and processes to support social ties, alternative course is the use of technology to supplant social ties - > think of this as organizing without the work of organizing, questions of who to trust, who pays, permitted to use the resources are managed by middleware.

Group work is an inevitable fact of org life.

• Medha Devare, Life Sciences and Bioinformatics Librarian, Mann Library, Cornell University

Idea of Virtual Organization: boundary crossing, pooling of competencies, participants or activities geographically separated, fluid, flat structure, participant equality

Library contributions: technology choices, tools; tech support/guidance; subject expertise; understanding of research landscape; vision - user needs of the future?

Examples of library support: VIVO, DataStar (supports data-sharing among researchers)

DataStar: Data Staging Repository: supports data sharing, esp during research process, promotes publishing or archiving to discipline specific data centers and/or to Cornell's DR. Nascent stage

Reinventing the library? Librarians as middle-ware to facilitate process of connecting and creating coherence across disciplines - both VIVO and DataStar aid this.

Hope that both tools seamlessly interact with each other.


D. Scott Brandt, Associate Dean for Research, Purdue University Library

Tries to embed librarians in research teams. We have to redefine what we do, collect.

When people evaluate services, they often consider factors like cost, features, reliability, and performance. For AI, we want to extend those factors by asking questions about how the AI model is built and its impact.

Register now: 28 February 2018
A webinar sponsored by COMSOL

The workshop is aimed at promoting innovation and technical expertise

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