Where is the opportunity for libraries in the collaborative data infrastructure?Susan ReillyProject ManagerLIBER

susan.reilly@kb.nl@skreilly

Contents

About LIBER Some context What is the collaborative data infrastructure? Introducing the researcher to the CDI Introducing the CDI to the researcher Now and next?

LIBER: reinventing the library of the future

Largest network of European reseach libraries: 450 in over 40 countries

Mission:

To provide an information infrastructure to enable research in LIBER institutions to be world class

Key performance areas

Scholarly communication and research infrastructures Reshaping the research library Advocacy

Advocacy

LIBER Projects

Reshaping The

research library

Scholarly Communication

&Research

Infrastructure

So why am I here?

Reshaping The

research library

Advocacy

Scholarly Communication

&Research

Infrastructure

Collaborative data infrastructure

What is the collaborative data infrastructure (scientific data infrastructure)?

…it’s about data

Not just the 20+ petabytes that the LHC at CERN produces every year

Increasing amount of digitised and born digital content in libraries

Increasing emphasis on open access publications and data: mandates, institutional repositories

Demand for data management support

Libraries in the data deluge

What is the collaborative data infrastructure?

“a broad, conceptual framework for how different companies, institutes, universities, governments and

individuals would interact with the system – what types of data, privileges, authentication or performance metrics should be planned. This framework would ensure the trustworthiness of data, provide for its curation, and

permit an easy interchange among the generators and users of data”

Now and Next

Authentication & authorisation New skills

Introducing the researcher to the CDI

Current situation ODE & linking data to publications Demand for data management support Advocacy

Opportunities for data exchange (ODE)

identify, collate, interpret and deliver evidence of emerging best practices in sharing, re-using, preserving and citing data, the drivers for these changes and barriers impeding progress, in forms suited to each audience

policy makers, funders, infrastructure operators, data centres, data providers and users, libraries and publishers

Steps to creating the conditions for data sharing

Understand data sharing today Collection of "success stories”, “near misses” and “honourable

failures” in data sharing, re-use and preservation

Data & scholarly communications Integrating data and publications Best practice in data citation New roles

Identify drivers and barriers Interviews with stakeholder

to seek consensus

Foto "Bell", Noordewierweg 116, Amersfoort.

Hypotheses

“Without the infrastructure that helps scientists manage their data in a convenient and efficient way, no culture of data sharing will evolve.”

Stefan Winkler-Nees (German Research Foundation, DFG)

Hypotheses by Category

4.Attitudes

6.Policies

8.Infrastructure

10.DMPs, Citability

11.Dependency on discipline

(1) Data contained and

explained within the article

(2) Further data explanations in

any kind of supplementary files to articles

(3) Data referenced from the article and

held in data centers and repositories

(4) Data publications, describing available datasets

(5) Data in drawers and on

disks at the institute

The Data Publication Pyramid

21

The Pyramid’s likely short term reality:

(1) Top of the pyramid is stable

but small(2) Risk that

supplements to articles turn into Data Dumping

places(3) Too many

disciplines lack a community

endorsed data archive

(4) Estimates are that at least

75 % of research data is

never made openly avaiable

22

The Ideal Pyramid

(1) More integration of text and data, viewers

and seamless links to interactive

datasets(2) Only if data

cannot be integrated in

article, and only relevant extra explanations

(3) Seamless links (bi-directional)

between publications and data, interactive

viewers within the articles

(4) More Data Journals that

describe datasets, data mgt plans and data methods

Issues for researchers

Researchers need somewhere to put data and make it safe for reuse

Researchers need to control its sharing and access Researchers need the ability to integrate data and

publication Researchers need to get credit for data as a first class research object Researchers need someone to pay for the costs of data availability and re-use

Library support for the researcher

Libraries and data centres must support…

data as first class research object: publishing, persistent identification/citation of datasets

data description, metadata, standards documentation and retrieval

proper documentation of data

long-term data archiving including data curation and preservation

Availability

Findability

Interpretability

Re-usability

Implications for libraries

Level of integration Implication for library

Data contained within the article

Data published in supplementary files to articles

Datasets referenced from the articles

Data published independently from written publications (“data publication”)

Data in drawers and on disks at the institute

Prepare for adequate preservation strategies

Presentation and preservation mechanisms

Persistent link

Citability of dataset Persistent link Perpetual access to dataset

Support publication process Curation of datasets Metadata and documentation

Engage in data management planning

Demand for data management support

Advocacy

“Many researchers do not appear to see the value and benefits of data citation. There is a gap, which could be

filled by libraries, in advocacy for data sharing, the use of subject specific repositories, and best practice in data citation. These, if filled, would increase the number of

researchers sharing and reusing data.”

http://www.alliancepermanentaccess.org/wp-content/plugins/download-monitor/download.php?id=Report+on+Best+Practices+for+Citability+of+Data+and+on+Evolving+Roles+in+Scholarly+Communication

Introducing the CDI to the researcher

Scoping the researcher’s requirements Collaboration & policy development

The AAA Study: a research passport

“evaluate the feasibility of delivering an integrated Authentication and Authorisation Infrastructure, AAI, to help the emergence of a robust platform for access to and preservation of scientific information within a Scientific Data Infrastructure (SDI)”

Now and Next

Authentication & authorisation New skills

Methodology

The Google Generation

Collaboration

“Networked science is on the rise, the researcher is no longer working alone in his office, he is working virtually

with other researchers from around the world. For them it is important that they can use the same software and

share and reuse the same content related objects, in a trusted environment.”

Heinke Neuroth, Head of Innovation, Goettingen State & University Library

Use Cases

1. Creating Data

2. Processing Data

3. Sharing Data

4. Preserving Data

5. Multi-disciplinary Data Services

6. Analysing Data

7. Accessing Data

8. Accessing Experiments and Data

Requirements…

Tracking of provenance, authenticity, integrity of the material Integration of researcher ID with institutional credentials Researchers’ self registration Securely linking researcher and data identifiers for tracking

provenance Delegation of identity management to home institute Attribute provisioning for users participating in specific research

projects managed by the specific research groups (VOs) Attribute aggregation Unification and homogenisation of identity federations´ attributes and

agreed levels of assurance in order to facilitate authorisation Accreditation of trusted identity Providers (IdPs), based on

international standards, depending on the required level of assurance Entitlement management to minimise the occurrence of events where

license monies are being paid twice without necessity (e.g., for access to scientific journals).

Technical infrastructure

Legal Recommendations

Need to protect the user

Collaboration & policy development

Policies for data sharing Values & Ecosystems Infrastructure & Technology Legal & Ethical Institutional Support

http://recodeproject.eu/

Now & next

What should our priorities be?

LIBER ten recommendations:http://www.libereurope.eu/news/ten-recommendations-for-libraries-to-get-started-with-research-data-management

1. Identify & develop skills

2.Collaborate

Alliance for Permanent Access to the Record of Science in Europe Network (APARSEN) look across the excellent work in digital preservation which is

carried out in Europe and to try to bring it together under a common vision

Trust! Sustainability! Usability! Access!

http://www.alliancepermanentaccess.org/

Engage

Thank you!

Any questions?