The Evidence Hub: Harnessing the Collective Intelligence of Communities to Bu...Anna De Liddo
Presentation to the Large-Scale Idea Management and Deliberation Systems Workshop @
6th International Conference on Communities and Technologies C&T2013
June 29,2013
Munich, Germany
From Data Platforms to Dataspaces: Enabling Data Ecosystems for Intelligent S...Edward Curry
Digital transformation is driving a new wave of large-scale datafication in every aspect of our world. Today our society creates data ecosystems where data moves among actors within complex information supply chains that can form around an organization, community, sector, or smart environment. These ecosystems of data can be exploited to transform our world and present new challenges and opportunities in the design of intelligent systems. This talk presents my recent work on using the dataspace paradigm as a best-effort approach to data management within data ecosystems. The talk explores the theoretical foundations and principles of dataspaces and details a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration of heterogeneous data sources. Finally, I share my perspectives on future dataspace research challenges, including multimedia data, data governance and the role of dataspaces to enable large-scale data sharing within Europe to power data-driven AI.
In recent years governments and research institutions have emphasized the need for open data as a fundamental component of open science. But we need much more than the data themselves for them to be reusable and useful. We need descriptive and machine-readable metadata, of course, but we also need the software and the algorithms necessary to fully understand the data. We need the standards and protocols that allow us to easily read and analyze the data with the tools of our choice. We need to be able to trust the source and derivation of the data. In short, we need an interoperable data infrastructure, but it must be a flexible infrastructure able to work across myriad cultures, scales, and technologies. This talk will present a concept of infrastructure as a body of human, organisational, and machine relationships built around data. It will illustrate how a new organization, the Research Data Alliance, is working to build those relationships to enable functional data sharing and reuse.
The Evidence Hub: Harnessing the Collective Intelligence of Communities to Bu...Anna De Liddo
Presentation to the Large-Scale Idea Management and Deliberation Systems Workshop @
6th International Conference on Communities and Technologies C&T2013
June 29,2013
Munich, Germany
From Data Platforms to Dataspaces: Enabling Data Ecosystems for Intelligent S...Edward Curry
Digital transformation is driving a new wave of large-scale datafication in every aspect of our world. Today our society creates data ecosystems where data moves among actors within complex information supply chains that can form around an organization, community, sector, or smart environment. These ecosystems of data can be exploited to transform our world and present new challenges and opportunities in the design of intelligent systems. This talk presents my recent work on using the dataspace paradigm as a best-effort approach to data management within data ecosystems. The talk explores the theoretical foundations and principles of dataspaces and details a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration of heterogeneous data sources. Finally, I share my perspectives on future dataspace research challenges, including multimedia data, data governance and the role of dataspaces to enable large-scale data sharing within Europe to power data-driven AI.
In recent years governments and research institutions have emphasized the need for open data as a fundamental component of open science. But we need much more than the data themselves for them to be reusable and useful. We need descriptive and machine-readable metadata, of course, but we also need the software and the algorithms necessary to fully understand the data. We need the standards and protocols that allow us to easily read and analyze the data with the tools of our choice. We need to be able to trust the source and derivation of the data. In short, we need an interoperable data infrastructure, but it must be a flexible infrastructure able to work across myriad cultures, scales, and technologies. This talk will present a concept of infrastructure as a body of human, organisational, and machine relationships built around data. It will illustrate how a new organization, the Research Data Alliance, is working to build those relationships to enable functional data sharing and reuse.
The digital transformation of research supportAlison McNab
Workshop delivered by Alison McNab & Andy Tattersall at the Northern Collaboration 2017 Conference at the University of York on 8 September 2017.
This workshop gave delegates an overview of the digital research landscape, an introduction to tools and resources to tame the landscape, the opportunity to consider the skillsets required in the context of their own workplace, and an introduction to the research technologist manifesto.
Strategies for Establishing Partnerships for Digital Preservationlljohnston
Strategies and success metrics for developing digital preservation partnerships. Presentation given at the 2013 Educating Stewards of the Public Information Infrastructure (ESOPI) Symposium.
ELPUB 2018 Feminist Open Science workshopLeslie Chan
This was the slides for the workshop on Feminist Open Science presented at ELPUB2018 in Toronto. Notes for the session is available here: https://docs.google.com/document/d/1zr51nZ4VRjVNLixeRc_4SPa-liSALADLTbJ1RUJYcpo/edit
"This workshop will centre on how current discourse around Open Science has tended to focus on the creation of new technological platforms and tools to facilitate sharing and reuse of a wide range of research outputs, but has largely avoided tackling many important issues related to inclusion of a diversity of perspectives in science. We believe a feminist perspective can help to surface these issues, particularly with regard to the need for inclusive infrastructure, which are especially important as Open Science increasingly becomes part of government agendas and policies. We expect that researchers, practitioners and policy makers interested in Open Science will benefit from this workshop to think about issues of inclusivity in Open Science that are not receiving sufficient attention. We expect participants who attend this workshop will gain awareness about relevant resources and work that has been done by feminist technoscience scholars to expand the perspectives of Open Science. We hope that participants will take away new possibilities for their work that they may not have considered before. For policy makers, this workshop will be particularly relevant to help think about how evidence for Open Science should be assessed from a more feminist inclusive standpoint. The workshop will also present results from a two-day workshop on Feminist Open Science that will take place prior to the ELPUB workshop, with the intent of soliciting feedback and collaboration."
Presentation by Laura Molloy and Ann Gow from (HATII) University of Glasgow at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
Bridging By Design: The Curation and Management of Digital Assets Specializa...DigCurV
Presentation by Katie Shilton, Michael Kurtz, Bruce Ambacher, Erik Mitchell, Douglas Oard, and Ann Weeks, University of Maryland at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
A presentation on an Enterprise WIki pilot as part of the dissertation towards an MSc in Knowledge Management which was presented at the IBM Connectr event in Dublin on June 3rd 2008.
Integrating Digital Curation in a Digital Library curriculum: the Internatio...DigCurV
Presentation by Anna Maria Tammaro University of Parma, Florence at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
From Data Platforms to Dataspaces: Enabling Data Ecosystems for Intelligent S...Edward Curry
The Real-time Linked Dataspace (RLD) is an enabling platform for data management for intelligent systems within smart environments that combines the pay-as-you-go paradigm of dataspaces, linked data, and knowledge graphs with entity-centric real-time query capabilities.
The RLD contains all the relevant information within a data ecosystem including things, sensors, and data sources and has the responsibility for managing the relationships among these participants.
It manages sources without presuming a pre-existing semantic integration among them using specialised dataspace support services for loose administrative proximity and semantic integration for event and stream systems. Support services leverage approximate and best-effort techniques and operate under a 5 star model for “pay-as-you-go” incremental data management.
Linked Data Love: research representation, discovery, and assessment
#ALAAC15
The explosion of linked data platforms and data stores over the last five years has been profound – both in terms of quantity of data as well as its potential impact. Research information systems such as VIVO (www.vivoweb.org) play a significant role in enabling this work. VIVO is an open source, Semantic Web-based application that provides an integrated, searchable view of the scholarly activities of an organization. The uniform semantic structure of VIVO-ISF data enables a new class of tools to advance science. This presentation will provide a brief introduction and update to VIVO and present ways that this semantically-rich data can enable visualizations, reporting and assessment, next-generation collaboration and team building, and enhanced multi-site search. Libraries are uniquely positioned to facilitate the open representation of research information and its subsequent use to spur collaboration, discovery, and assessment. The talk will conclude with a description of ways librarians are engaged in this work – including visioning, metadata and ontology creation, policy creation, data curation and management, technical, and engagement activities.
Kristi Holmes, PhD
Director, Galter Health Sciences Library
Director of Evaluation, NUCATS
Associate Professor, Preventive Medicine-Health and Biomedical Informatics
Northwestern University Feinberg School of Medicine
The digital transformation of research supportAlison McNab
Workshop delivered by Alison McNab & Andy Tattersall at the Northern Collaboration 2017 Conference at the University of York on 8 September 2017.
This workshop gave delegates an overview of the digital research landscape, an introduction to tools and resources to tame the landscape, the opportunity to consider the skillsets required in the context of their own workplace, and an introduction to the research technologist manifesto.
Strategies for Establishing Partnerships for Digital Preservationlljohnston
Strategies and success metrics for developing digital preservation partnerships. Presentation given at the 2013 Educating Stewards of the Public Information Infrastructure (ESOPI) Symposium.
ELPUB 2018 Feminist Open Science workshopLeslie Chan
This was the slides for the workshop on Feminist Open Science presented at ELPUB2018 in Toronto. Notes for the session is available here: https://docs.google.com/document/d/1zr51nZ4VRjVNLixeRc_4SPa-liSALADLTbJ1RUJYcpo/edit
"This workshop will centre on how current discourse around Open Science has tended to focus on the creation of new technological platforms and tools to facilitate sharing and reuse of a wide range of research outputs, but has largely avoided tackling many important issues related to inclusion of a diversity of perspectives in science. We believe a feminist perspective can help to surface these issues, particularly with regard to the need for inclusive infrastructure, which are especially important as Open Science increasingly becomes part of government agendas and policies. We expect that researchers, practitioners and policy makers interested in Open Science will benefit from this workshop to think about issues of inclusivity in Open Science that are not receiving sufficient attention. We expect participants who attend this workshop will gain awareness about relevant resources and work that has been done by feminist technoscience scholars to expand the perspectives of Open Science. We hope that participants will take away new possibilities for their work that they may not have considered before. For policy makers, this workshop will be particularly relevant to help think about how evidence for Open Science should be assessed from a more feminist inclusive standpoint. The workshop will also present results from a two-day workshop on Feminist Open Science that will take place prior to the ELPUB workshop, with the intent of soliciting feedback and collaboration."
Presentation by Laura Molloy and Ann Gow from (HATII) University of Glasgow at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
Bridging By Design: The Curation and Management of Digital Assets Specializa...DigCurV
Presentation by Katie Shilton, Michael Kurtz, Bruce Ambacher, Erik Mitchell, Douglas Oard, and Ann Weeks, University of Maryland at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
A presentation on an Enterprise WIki pilot as part of the dissertation towards an MSc in Knowledge Management which was presented at the IBM Connectr event in Dublin on June 3rd 2008.
Integrating Digital Curation in a Digital Library curriculum: the Internatio...DigCurV
Presentation by Anna Maria Tammaro University of Parma, Florence at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
From Data Platforms to Dataspaces: Enabling Data Ecosystems for Intelligent S...Edward Curry
The Real-time Linked Dataspace (RLD) is an enabling platform for data management for intelligent systems within smart environments that combines the pay-as-you-go paradigm of dataspaces, linked data, and knowledge graphs with entity-centric real-time query capabilities.
The RLD contains all the relevant information within a data ecosystem including things, sensors, and data sources and has the responsibility for managing the relationships among these participants.
It manages sources without presuming a pre-existing semantic integration among them using specialised dataspace support services for loose administrative proximity and semantic integration for event and stream systems. Support services leverage approximate and best-effort techniques and operate under a 5 star model for “pay-as-you-go” incremental data management.
Linked Data Love: research representation, discovery, and assessment
#ALAAC15
The explosion of linked data platforms and data stores over the last five years has been profound – both in terms of quantity of data as well as its potential impact. Research information systems such as VIVO (www.vivoweb.org) play a significant role in enabling this work. VIVO is an open source, Semantic Web-based application that provides an integrated, searchable view of the scholarly activities of an organization. The uniform semantic structure of VIVO-ISF data enables a new class of tools to advance science. This presentation will provide a brief introduction and update to VIVO and present ways that this semantically-rich data can enable visualizations, reporting and assessment, next-generation collaboration and team building, and enhanced multi-site search. Libraries are uniquely positioned to facilitate the open representation of research information and its subsequent use to spur collaboration, discovery, and assessment. The talk will conclude with a description of ways librarians are engaged in this work – including visioning, metadata and ontology creation, policy creation, data curation and management, technical, and engagement activities.
Kristi Holmes, PhD
Director, Galter Health Sciences Library
Director of Evaluation, NUCATS
Associate Professor, Preventive Medicine-Health and Biomedical Informatics
Northwestern University Feinberg School of Medicine
LIBER Webinar: Turning FAIR Data Into RealityLIBER Europe
These slides relate to a LIBER Webinar given on 23 April 2018. Turning FAIR Data Into Reality — Progress and Plans from the European Commission FAIR Data Expert Group.
In this webinar, Simon Hodson, Executive Director of CODATA and Chair of the FAIR Data Expert Group, and Sarah Jones, Associate Director at the Digital Curation Centre and Rapporteur, reported on the Group’s progress.
This presentation was provided by Chris Erdmann of Library Carpentries and by Judy Ruttenberg of ARL during the NISO virtual conference, Open Data Projects, held on Wednesday, June 13, 2018.
Presentation investigating the state of FAIR practice and what is needed to turn FAIR data into reality given at the Danish FAIR conference in Copenhagen on 20th November 2018. https://vidensportal.deic.dk/en/Programme/FAIR_Toolbox_Nov2018 The presentation reflect on recent FAIR studies and international initiatives and outlines the recommendations emerging from the European Commission's FAIR Data Expert Group report - http://tinyurl.com/FAIR-EG
Decentralised identifiers and knowledge graphs vty
Building an Operating System for Open Science: data integration challenges, Dataverse data repository and knowledge graphs. Lecture by Slava Tykhonov, DANS-KNAW, for the Journées Scientifiques de Rochebrune 2023 (JSR'23).
Openness, exchange, FAIR DATA – oh brave new world that has such vision! (Dr....ETH-Bibliothek
Openness, exchange, FAIR data - oh brave new world. For some researchers, this is no longer a vision but already their day-to-day reality. For many others, however, terms like ‘open’, ‘FAIR data’* or ‘data exchange’ pose a challenge. What contribution can we make to ensure that new data comply with the FAIR Data Principles, and how can we measure the FAIRness of existing data? “Trust” is a key aspect: Trust that others interpret ‘your’ data correctly for example, or trust in data repositories.
The current status of Linked Open Data (LOD) shows evidence of many datasets available on the Web in RDF. In the meantime, there are still many challenges to overcome by organizations in their journey of publishing five stars datasets on the Web. Those challenges are not only technical, but are also organizational. At this moment where connectionist AI is gaining a wave of popularity with many applications, LOD needs to go beyond the guarantee of FAIR principles. One direction is to build a sustainable LOD ecosystem with FAIR-S principles. In parallel, LOD should serve as a catalyzer for solving societal issues (LOD for Social Good) and personal empowerment through data (Social Linked Data).
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Innovative Methods in Media and Communication Research by Sebastian Kubitschk...
The importance of FAIR and the Community of Data Driven Insights - the road to the science of the future
1. The importance of Data-Driven Communities
Road to the next Science
Carlos Utrilla Guerrero (Data Scientist)
c.utrillaguerrero@maastrichtuniversity.nl
3. “
This is perhaps an old, globally
and persistent question. The
transition towards the Next
Science can happen through
Open and FAIR principles
How can we make a better science?
CDDI Commentary (Draft): https://docs.google.com/document/d/1VQ7hBd8UOdvjGec2BwwCjC2cO3k6b9CU9NQsySh8MT0/edit?usp=sharing
4. “
No-one ever said FAIR was easy, but we have
to go through the hardship of making our
resources FAIR to enable better science
together. It benefits everyone to make it as
easy as possible for communities to make steps
in the direction of optimally achievable
FAIRness in their domain. - pag. 26*
Opinions of the original creators of the FAIR principles*
* FAIR Principles: Interpretations and Implementation Considerations (2020): https://doi.org/10.1162/dint_r_00024
5. Cathedral thinking - commitment to long-term visions
Leonardo Da Vinci
conceptualized the idea of
people being able to fly 400
years
Sagrada Familia, Spain.Gaudí began designing the structure in
1882, inspired by a far-reaching vision that extended well
beyond his lifetime. Construction on the church is scheduled to
wrap up in 2026.
Taking long-term thinking to a whole new level:
seven generations!
The foundations in success to Next Science
6. Enablers of discovery and innovations
Starting point of the journey: Open Science and FAIR
Preliminary report on the first draft of the Recommendation on Open Science
7. Google Trends: FAIR Data topic
https://trends.google.com/trends/explore?date=today%205-y&q=%2Fg%2F11g88dlvw4
8. Google Trends: FAIR Data topic
https://trends.google.com/trends/explore?date=today%205-y&q=%2Fg%2F11g88dlvw4
9. Visualising the relationship between concepts
Starting point of the journey: Open Science and FAIR
https://trends.google.com/trends/explore?date=today%205-y&q=%2Fg%2F11g88dlvw4,%2Fm%2F025ttdm,
%2Fm%2F0j9kvph
11. An international, bottom-up paradigm for
the discovery and reuse of digital content
by and for people and machines
12. FAIR principles do not dictate specific technological implementations, rather provide
guidance for improving...:
1. Findability, by globally unique, persistent identifier, rich metadata and indexed for
search.
2. Accessibility, retrievable using standardised, open protocol that specify access
restrictions where necessary.
3. Interoperability, meta-data use a formal, accessible, shared and broadly for
knowledge representation using FAIR vocabularies and qualified links to other
resources.
4. Reusability accurate and relevant attributes, provenance, and data usage license,
meet domain-relevant community standard.
...of digital resources.
Software
Metadata
Data
13. Community For Data Driven Insights (CDDI)
Building the road to the science of the future
c.utrillaguerrero@maastrichtuniversity.nl
14. Towards FAIR University: from principle to practise
Showcases to prove concept across disciplines
Check the conceptual map here:
https://embed.kumu.io/6a045ad6e4c091c5bf4600de8a
f94d5f#untitled-map/ludeme
16. Ludeme Summary
● What?
○ Computational study
○ World’s traditional games
○ Recorded human history
● Objectives
1. Model: Full range of traditional games in a single
playable database
2. Reconstruct: Missing knowledge about games
more accurately
3. Map: Spread of games and assoc. mathematical
ideas through history
● Question:
○ Can we use modern computational techniques to
help improve our understanding of ancient
culture?
Slides Cameron Browne, 2018 http://www.ludeme.eu/outputs/browne-bgs-2018.pdf
17. Digital Ludeme Portal, one solution to a FAIR dataset
“DLP Database illustrates how we are obtaining this data and storing it in a consistent format both for
use within the Digital Ludeme Project and for the benefit of other researchers and practitioners,
and how we are adopting FAIR principles to make this database as reliable, accessible and useful as
possible. - Matthew Stephenson et al 2020
18. DLP Database path of FAIRness
DLP database is fully
public and available to
access in php server that
support sql
File with all variables,
naming convention,
descriptions, raw and
transformed data
codebook/data dictionary.
Documentation and
readme with release
version, tutorials, license
and user guide.
Explaining ETL (extract,
transform, load)
Unambiguous identification
of games.
https://ludii.games/identifier?Id=
DLP.Games.427
Luddi Dataset
19. Partly FAIR may be fair enough but let's improve it!
URL Persistent schemas
Searchable major engine
Use FAIR vocabularies and
qualified links
Resource identifier: https://ludii.games/library.php
Record provenance and
follow community-standards
20. Research excellence and the Lawgex Project
How to implement FAIR is particular and
unique to the community in which you are
doing your research - Kody Moodley
21. Challenge accepted - create a FAIR solution and share with others
Existing technologies such Semantic Web are widely
accepted to adhere with Interoperability principle
It's also about how we share our solution:
#fairsolution are everywhere, reuse solutions from
existing implementations.
And that's absolutely what we want:
● FAIR Vocabulary using EuroVoc
● Enriched with new terms using RDF standards
● Use Linked Open Data to fulfil FAIR
TO HARMONIZE THE MEANING OF INFORMATION
22. FAIR software tools:
This solves the “works on my computer, but not on
yours” problem by packaging all the necessary
software dependencies and operating system
resources required by an application in one
independent software “container”.
Let’s start using reproducible research tools
text data code version
Next
Science
PDF
reproducibility
spectrum
0% 100%
23. ● Human:
○ “What you can’t measure, you can’t
improve it” - Peter Drucker
○ Reward and prestige experience
○ Share personas responsibilities
accordingly
● Technical:
○ Lack of catalog of tools per faculty
○ Absence of data management
guidelines
○ Lack of documentation
● Human:
○ Inclusive with diverse paths to FAIR
○ Community: Permissive culture
○ Individuals: Ownership and
engagement
● Technical:
○ Human-centric design (user friendly
interface for all)
Drivers:
Personas = data stewards, data scientist, researchers, data engineers, phd & master & bachelor students, PI, software
developers, Managers
Barriers:
24. We must find a way to understand intentions,
behaviour and motivations to apply FAIR to be able to
generate the next services focusing on the personas.
Personas = attract different people of
diverse backgrounds, desires. skills and experiences
Lesson 1: Empathy
25. Lesson 2: The “art of planning into distant distant future”
but...
“the need of long-term thinking is a matter of utmost urgency, requiring
immediate action in the present.” - The Good Ancestor 2021 p.6
26. “
What kind of University will our
next generation like to come?
We will find this answer together
but typically the response root is
directed to education.
Lesson 3: FAIR and Data Science Literacy
CDDI Commentary (Draft): https://docs.google.com/document/d/1VQ7hBd8UOdvjGec2BwwCjC2cO3k6b9CU9NQsySh8MT0/edit?usp=sharing
27. A little progress over the last year and still work remains!
but concrete actions were done:
● FAIR Events and Workshops
● Lessons learned
Next year will focus:
● Personas engagement
● Increase FAIR and Data Science literacy
Crucial to connect CDDI showcases with data scientist community CDDI
Cathedral thinking (aka. long -term work towards FAIR University)
Summary and outlook
28. Thank you
You can find me at:
c.utrillaguerrero@maastrichtuniversity.nl
