Data Management Plans based on digital workflow models: A report on a DMP project within the frame of e-Infrastructures Austria Paolo Budroni, Barbara

Data Management Plans based on digital workflow models:

A report on a DMP project within the frame of e-Infrastructures Austria

Paolo Budroni, Barbara Sánchez Solís

University of Vienna

Budroni, Sánchez 2 e-Infrastructures Austria – London June 2015

WORLDS OF DATA :

ABOUT RESEARCH DATA

ABOUT DATA


The LERU Roadmap for Research Data presents the following sets this context (*) :

“Research data, from the point of view of the institution with a responsibility for managing the data, includes:

•All data which is created by researchers in the course of their work, and for which the institution has a curational responsibility for at least as long as the code and relevant archives/ record keeping acts require, and

•third-party data which have originated within the institution or come from elsewhere.”

(*) LERU Research Data Workingg Group, Advice Paper No. 14 – December 2014


The Australian Griffith University presents the following definition (*) :

“Research data are factual records, which may take the form of numbers, symbols, text, images or sounds, which are used as primary sources for research, which are commonly accepted in the research community as necessary to validate research findings.”

(*) Ingrid Dillo – Data Archiving and Networked Services (DANS), Certification as a means of providing trust, Florence, Fondazione Rinascimento Digitale, 2012


The University of Minnesota about research data (*):

Research data are data in any format or medium that relate to or support research, scholarship, or artistic activity. They can be classified as: • Raw or primary data: information recorded as notes, images, video footage, paper surveys, computer files, etc.• Processed data: analyses, descriptions, and conclusions prepared as reports or papers• Published data: information distributed to people beyond those involved in data acquisition and administration

According to this logic we identify:

Different levels (or “layers”) of processing dataThis has an impact on the digital workflow model

(*) Ingrid Dillo – Data Archiving and Networked Services (DANS), Certification as a means of providing trust, Florence , Fondazione Rinascimento Digitale, 2012

World of data Raw data (primary data) World of data Raw data (primary data)

Processed Data Negative Results Processed Data Negative Results

Processed DataProcessed Data

Processed Data Inconclusive Results

Processed Data Inconclusive Results


Processed DataProcessed DataShared

DataShared

Data


Positive resultsPositive results

Positive resultsPositive results

Shared Data

Shared Data

Shared Data

Shared Data

Pub. DataPub. Data

OA

Pub. DataPub. DataReleased

DataReleased

Data

Different levels of processing of dataModel for digital archiving

Ensuring legal and ethical compliance is key issue in this context


Levels / layers in processing of data

Raw data, primary data

Processed Data (positive, negative and inconclusive results)

Shared Data and Published Data

Open Access Published Data


Open Data Shared Data and Reused Data

Published Data

Restricted Data

Strata of research data


THE DIGITAL WORKFLOW


WORKFLOW MODEL

SEGMENTS


Digital workflow model

Preingest Ingest Rep-Management Re-Use

archives

Ensuring legal and ethical compliance is key issue in this context

Metadata

File

License

Persistent Identifier

#

ExternalSystems

All types of data

Processes

DA

TA

PR

OV

IDE

RS

DMP – along all processes

Ontology of ObjectsDifferent Types

COMMON LEGAL SPACE


SETUP OF A REFERENCE

ARCHITECTURE

FOR RESEARCH DATA MANAGEMENT

ROLE MODELS


FOUR MAIN ACTORS INVOLVED IN THE MGMT OF RESEARCH DATA

THE STAKEHOLDERS

Research LibrariesIT-Services

Researchers Funders / Funding Services


FOUR MAIN ACTORS ARE INVOLVED IN THE MGMT OF RESEARCH DATA

FOUR STAKEHOLDERS

Research Libraries IT-Services

Researchers Funders / Funding services

Data Management Plans


Different views – different roles, responsibilities, competencies

ARCHIVE SAFEGUARDING

CONTENT SUPPLIER

FUNDING BODY

QUALITY

SOCIAL RESPONSIBILITY

ROLE RESPONSIBILITY

INSTITUTION LEGAL SECURITY


PUBLISHER ? SAFEGUARDING ?

ARCHIVE SAFEGUARDING

CONTENT SUPPLIER

FUNDING BODY

QUALITY

SOCIAL RESPONSIBILITY

ROLE RESPONSIBILITY

INSTITUTION LEGAL SECURITY

Different views – different roles, responsibilities, competencies


DMP PILOT

ON A NATIONAL LEVEL


Premises

• Univ. of Vienna: Document on the creation of DMPs Reasons for DMPs Consideration of different project stages (processes) Forms of DMPs Checklist

• 5 workshops in different partner institutions Target groups: librarians, IT, research support


DMP pilot on national level

• DMP focussed on Horizon 2020

• Based on DCC checklist for a Data Management Plan, v4.0

• Customised to actual institution

• Goal: Align DMP with existing local infrastructures and services

• Procedure Run pilot with 7 different faculties at University of Vienna Optimisation according to feedback Extend pilot to other institutions in Austria

• 5 workshops in different partner institutions Target groups: librarians, IT, research support




Characteristics

• Execution on a national level (20 Austrian universities)

• Support of dialogue with different scientific communities

• Common approach may lead to Development of national services in non-technical areas Pooling of competencies at a national level Development of systems apart from DMPonline

• Administration of data stays with institutions• Frame/design of DMP can be changed (e.g. inclusion of

text modules, drop down menus etc.)• Extraction of data can be optimised

• DMP requires constant adaptation and adjustment

• Archiving strategies involve more parties than originally assumed (planning of resources)

• Business re-engineering in research support services: Data security management, storage, metadata modelling,

ethical and legal issues

• New job profiles: data scientists, data librarian


First Conclusions

• Extension of language area

• DMP requires constant adaptation and adjustment

• Archiving strategies involve more parties than originally assumed (planning of resources)

• Business re-engineering in research support services Data security management, storage, metadata modelling,

ethical and legal issues

• New job profiles: data scientists, data librarian

• Further support services required


Challenges

• Who is the owner of DMPs?

• Who administrates DMPs?

• Who reviews DMPs (institutional/national/European level?)

• What about projects beyond H2020?

• What about existing projects and the preservation of the data?


University of Vienna

Library and Archive ServicesPaolo Budroni, [email protected]

Barbara Sánchez Solís, [email protected]

Computer CentreRaman Ganguly, [email protected]

José Luis Preza, [email protected]

[email protected] www.e-infrastructures.at

e-Infrastructures Austria

Thanks!

Documents

Data Management Plans based on digital workflow models: A report on a DMP project within the frame of e-Infrastructures Austria Paolo Budroni, Barbara