A Component of Professional Skills Workshops for Graduate Research Students

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(1)A Component of Professional Skills Workshops for Graduate Research Students. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1.

(2) Seminar presenters  Ernie Boyko, Carleton University  Wendy Watkins, Carleton University. The Carleton University Library Data Centre http://www.library.carleton.ca/find/data. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2 2.

(3) Outline Part I and II . Part I February 1, 2012   . . . Part II February 2, 2012    . 06/03/2012. Introduction to research data An overview of research data management Quick summary of the international/national/local situation Developing a research data plan Hands-on exercises Explains what should you do Discussion Summing up Research Data Management Seminar, February 1-2, 2012, Carleton University. 3.

(4) Objectives of the seminar  A gentle introduction to research data management  Concepts  Principles  Importance  Why this seminar?  Research data management has become an integral part of the research process . As graduate students, you need to be aware of data management for your current work and for the future.  Research data management is increasingly on the agenda of various. national and international organizations   .  06/03/2012. Research funding councils National Data Summit September, 2011 CODATA involvement in the International Polar Year (IPY) data management strategy. Carleton has been a strong player on the data front. Research Data Management Seminar, February 1-2, 2012, Carleton University. 4 4.

(5) Research Data  What do we mean by research data?. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 5.

(6) Definition of research data  Research data are digital information, structured through methodology for the purpose of producing new knowledge.  Not all digital information is research data, but all have the potential to become research data.  Digital Information + Methodology = Research data which can be used to produce new knowledge 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 6 6.

(7) ENRON example  An example of digital information that became research data can be found in Enron’s email.  As email they were NOT research data; they were merely messages in inboxes.  However, when subjected to a link analysis, the results became research data that produced knowledge of the communications web between the parties.  The new knowledge produced had a significant impact - several jail terms! 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 7 7.

(8) Diesner, Jana and Kathleen M. Carley. Exploration of Communication Networks From the Enron Email Corpus. In Proceedings of the SIAM International Conference on Data Mining, Workshop on Link Analysis, pp. 3-14, Counterterrorism and Security, Newport Beach, CA, April 2005. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 8.

(9) Numeric information Raw Data • numeric files created. and organized for analysis/processing • requires processing • not display-ready. Statistics • numeric facts/figures • created from data, i.e,. already processed • presentation-ready 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 9 9.

(10) Scope of research data  Research data are generated in many different. domains.  Social sciences, humanities, natural sciences, engineering,. etc..  The methods and the processes for creating and. using the data may vary.  For example, the humanities work from primary sources.  But the role of research data and the vision that. information scientists have for its management are consistent  There is a widely-based worry about the state of the world’s data 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1010.

(11) “Scientific data are not homogenous in any manner. The disciplines generating data have widely varying practices with respect to the reporting of experimental, observational and calculation conditions and the resulting metadata. Archiving practices, in terms of direct deposition into community databases, inclusion in peer-reviewed papers, etc. differ greatly. Yet because almost all data are generated and managed electronically, the dream exists of making everything available.”. John Rumble, Jr. Past-president of CODATA International. Information International Associates, Inc. 2006 CODATA conference, Beijing, http://www.codata.org/06conf/keysessions.html#I3. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1111.

(12) Research Data  Why are research data important?. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 12.

(13) Why are research data important? “Data are unlike other tools of the research endeavour. They provide the raw material from which information and knowledge can be created. By their nature, data allow for exploration of topics of interest to the researcher. Unlike printed tables which, like a postcard, provide a picture of one view of a larger phenomenon, data can act as a camera, allowing the researcher to manipulate the background, change the foreground and more fully investigate the object under study.” Watkins, Wendy, and Ernie Boyko, "Data Liberation and Academic Freedom" Government Information in Canada/Information gouvernementale au Canada 3, no. 2 (1996). [http://www.usask.ca/library/gic/v3n2/watkins2/watkins2.html]. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1313.

(14) Research data are assets.  They support the original research  They increase in value if they can be repurposed. and shared with other researchers  Research data can be shared in a number of ways:.  informally, from researcher to researcher, on a peer-. to-peer basis  deposit in a self-archiving system  deposit in a specialist data centre, dedicated to archiving, preserving and disseminating digital data  deposit in an institutional repository 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1414.

(15) Research Data Management?  What do we mean by research data management?. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 15.

(16) Research Data Management  RDM involves the application of sound practices in. the creation of data for current and future purposes  Also referred to as data curation which is the. preservation and maintenance of digital assets  Data stewardship.  RDM as a national strategy in Canada is a mere infant. at best.  National working groups have sought the development. of a national plan for over a decade  The current seminar with you as researchers is an attempt at a grassroots approach 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 16.

(17) A Paradigm for Data Management  The lifecycle of data is a representation of the various stages through which data flow from production to use to preservation to new uses of the data.  Each stage consists of a set of related activities that culminate in a significant product, which is then passed to a subsequent stage.  By linking together a series of stages in logical sequence, the processes of data production and use are described. 06/03/2012. Adapted from C. Humphrey, “Data Library Services in the Data Stewardship Lifecycle,” TICER Digital Libraries å laManagement Carte 2009. http://www.tilburguniversity.nl/services/lis/ticer/09carte/index.html Research Data Seminar, February 1-2, 2012, Carleton University. 1717.

(18) Traditional research/ knowledge-creation lifecycle. Study concept and design. Data Collectio n. Data Processin g. Analysis. Access and Disseminatio n. Research Outcomes. Public Space 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1818.

(19) Lifecycle of data and research  The stages in the data lifecycle can be. aggregated or disaggregated into larger or smaller groupings, depending on the viewpoint one desires.  Keep these points in mind while examining a couple of lifecycle representations.  The first model is the data lifecycle  From there we will move to the research lifecycle Adapted from C. Humphrey, “Data Library Services in the Data Stewardship Lifecycle,” TICER Digital Libraries å la Carte 2009. http://www.tilburguniversity.nl/services/lis/ticer/09carte/index.html. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 1919.

(20) Traditional research /knowledge-creation lifecycle with repurposing of data for reuse in research. Data Discovery. Study concept and design. Data Collection. Data Repurposing. Data Processing. Analysis. Access and Dissemination. Research Outcomes. Public Space 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2020.

(21) Traditional research/knowledge-creation lifecycle with repurposing of data and repository for data research: data stewardship. Data Repurposin g. Data Discovery. Study concept and design. Data Collectio n. Data Processin g. Analysis. Data Repository. Access and Disseminatio n. Research Outcomes. Public Space 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2121.

(22) Research Data Management?  What are the benefits of research data management. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 22.

(23) Re-use of data  Confirmation of original findings  Replication of results  Prevention of research fraud  They are essential for you to defend your research  Further research  Answering questions not undertaken in the original study  Teaching  Often used in teaching statistical methods  Planning follow-up studies  Building on the original data by introducing a time factor  Conducting trend analyses  Eg. Unemployment rate; data are collected in the same way over time and analysed as a time series 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2323.

(24) Research Data Management A few words about the bigger picture  International  National. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 24.

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(27) Data stewardship principles OECD (2004) Ministerial Declaration on Access to Publicly Funded Research Data •. openness, transparency, legal conformity, protection of intellectual property, formal responsibility, professionalism, interoperability, quality & security, efficiency and accountability.. OECD (2007) Principles and Guidelines for Access to Research Data from Public Funding •. 06/03/2012. sustainable preservation and archiving are key to fulfilling formal responsibility, professionalism, quality & security, efficiency and accountability. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2727.

(28) Data stewardship principles U.K. Research Information Network (2008) Stewardship of digital research data: a framework or principles and guidelines • •. • • •. 06/03/2012. roles and responsibilities interoperability, standards and quality assurance access, usage and credit benefits and cost effectiveness preservation and sustainability. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2828.

(29) Data stewardship principles. U.S. Interagency Working Group on Digital Data (2009) Harnessing the Power of Digital Data for Science and Society • • •. •. •. •. • 06/03/2012. science is global and thrives in the digital dimensions; digital scientific data are national and global assets; not all digital scientific data need to be preserved and not all preserved data need to be preserved indefinitely; communities of practice are an essential feature of the digital landscape; preservation of digital scientific data is both a government and private sector responsibility and benefits society as a whole; long-term preservation, access, and interoperability require management of the full data lifecycle; and dynamic strategies are required. Research Data Management Seminar, February 1-2, 2012, Carleton University. 2929.

(30) Alliance of German Science Organizations (2010) Principles for the handling of research data*  .    . Security and accessibility. Different scientific disciplines must take responsibility for the forms and conditions of access to research data in their respective disciplines. Scientific recognition for data management. Teaching and training for professional data management. Use of standards. A sustainable development of infrastructure.. * Not an official translation. 06/03/2012. Research Data Management Seminar, February 1-2, Research Data Management 2012, Carleton University Seminar, April 12, 2010, Toronto. 3030.

(31) What about Canada?  We are not moving along with our US and European colleagues. ……..but this not for a lack of trying!  Some Canadian efforts have included:.  National Data Archive Consultation (NDAC) (2000-2002)  National Consultation on Access to Scientific Research Data. (NCASRD) (2004-2006).  Canadian Digital Information Strategy (CDIS) (2006-2007).  CARL Data Management Working Group  Research Data Canada: Research Data Strategy Working. Group.  National Data Summit September, 2011  CODATA involvement in the International Polar Year (IPY). data management strategy. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 31.

(32) Gap analysis results for Canada. Source: The Stewardship of Research Data in Canada: a gap analysis, Table 2, page 17. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 3232.

(33) . Moderate Gaps o Policies:. ▪ Ideal: National comprehensive, coherent data management policy ▪ Real: Some policies from tri-Council. o Standards. ▪ Ideal: Widespread adherence to standards ▪ Real: DDI and XML in the social sciences. o Research and Development. ▪ Ideal: Coordinated approach in terms of data stewardship ▪ Real: Unconnected projects looking at different issues. o Access. ▪ Ideal: Widespread access to publicly-funded research data ▪ Real: While many organizations still charge for data, there are projects like Geo-connections that are leading the way Research Data Management Seminar, December 2, 2010, Regina, SK. 33.

(34) . Large gaps (1) o Funding. ▪ Ideal: Funding covers data lifecycle including long-term support ▪ Real: Costs for data management are not supported. o Roles and Responsibilities. ▪ Ideal: Clearly defined and properly filled ▪ Real: No lines of custodial responsibility along the research data lifecycle. o [Trusted digital] data repositories. ▪ Ideal: Comprehensive network of trusted digital repositories ▪ Real: Large gaps in both coverage and capacity Research Data Management Seminar, December 2, 2010, Regina, SK. 34.

(35) . Large gaps (2) o Skills and Training. ▪ Ideal: Data Stewardship skills are widespread and supported by data scientists, information professionals and researchers ▪ Real: Insufficient numbers of data scientists and information professionals; researchers do not understand the process. o Reward and recognition system. ▪ Ideal: Reward systems recognize data as a contribution to research ▪ Real: Little recognition of the value of data stewardship; disincentives in some disciplines for data sharing. o Preservation. ▪ Ideal: Data preserved using standards-based, active management practices and stored in trusted digital repositories ▪ Real: Researchers lack skills; preservation is not a priority; lack of skilled professional data managers Research Data Management Seminar, December 2, 2010, Regina, SK. 35.

(36) CNC/CODATA. The Committee on Data for Science and Technology.  Producing “Data Activities in Canada”  A list of scientific and social-science data projects  Sangster Award  Enables graduate student to attend the biennial CODATA conference  Objective: to help foster and advance science and technology through developing and sharing knowledge about data and data-related activities  Endorsing this type of seminar  Developing a research data management seminar for researchers  Developing a pre and post-seminar questionnaire for researchers. on data management activities and attitudes  Coordinating the International Polar Year RDM project 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 3636.

(37) Canadian IPY Pilot.  Establish an archival backbone between OCUL Scholars Portal and the University of Alberta Libraries.  Apply for a lightpath loop on the CANARIE optical high-speed research network connecting both centres.  Start with replication and storage microservices.  Add micro-services to expand the functionality of the IPY pilot community cloud. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 37.

(38) Ontario College and University Libraries  OCUL Data Group proposed and implemented a. project called <ODESI> (Ontario Data Documentation, Extraction Service and Infrastructure).  It is the basis for the data centre service here at. Carleton and the other Ontario Universities  It works in conjunction with Scholars Portal  If it were able to become a trusted Digital Repository, it could become a hub for managing Canada’s social science data.. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 38.

(39) Scale of the challenge for Canada and Others “The scale of the challenge regarding the stewardship of digital data requires that responsibilities be distributed across multiple entities and partnerships that engage institutions, disciplines, and interdisciplinary domains” Pam Bjornson, DG, CISTI and Chair of the RDSWG. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 3939.

(40) Your Part of the Challenge  As young researchers starting out you  Will have the tools to enable you to meet the new requirements of funding agencies  Will have the knowledge to promote best practices in research data management  Will never suffer a ‘data catastrophe’ and lose your research  Will have a bona fide answer to any questions regarding the integrity of your research. 06/03/2012. Research Data Management Seminar, February 1-2, 2012, Carleton University. 40.

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