Facilitate Open Science Training for European Research Focus on data management plans – policies, requirements, resources, examples Martin Donnelly, Digital Curation Centre, University of Edinburgh OVERVIEW 1.  Data Management Plans and Planning 2.  Policies overview (UK, USA, Australia) 3.  DMP in Horizon 2020 (pilot overview and specifics) 4.  Support and resources Facilitate Open Science Training for European Research 1. Data management plans and planning 1a. DMP overview •  Research funders often ask for a data management plan (DMP) to be submitted alongside grant applications and/or developed over the course of the research project. (HEIs are increasingly asking their researchers to do this too…) •  A DMP is (usually) a short document detailing specifics of the data that will be created during a research project, together with information on how it can be accessed and utilised •  Data management planning is the process of planning, describing and communicating the activities carried out during the research lifecycle in order to… •  Keep sensitive data safe •  Maximise data’s reuse potential •  Support longer-term preservation •  Data management planning underpins and pulls together different strands of data management activities, often across multiple project partners 1b. Benefits of data management planning •  It is intuitive that planned activities stand a better chance of meeting their goals than unplanned ones. The process of planning is also a process of communication, increasingly important in interdisciplinary/multi-partner research. Collaboration will be more harmonious if project partners (in industry, other universities, other countries…) are on the same page •  In terms of data security, if there are good reasons not to publish/share data, in whole or in part, you will be on more solid ground if you flag these up early in the process •  DMP also provides an ideal opportunity to engender good practice with regard to (e.g.) file formats, metadata standards, storage and risk management practices, leading to greater longevity of data, and improved quality standards… Limits of data management planning What can a plan not do? It can’t do the work for you. The map is not the territory (Korzybski) or Chalk’s no shears (Scottish saying) It is important to remember that the human challenges in data management are often more difficult to meet than the technological ones. Communication is vital. 1c.  What  does  a  data  management  plan  look  like?   A  brief  statement  defining:     ?  how  data  will  be  captured/created   ?  how  it  will  be  documented   ?  who  will  be  able  to  access  it   ?  where  it  will  be  stored   ?  how  it  will  be  backed  up,  and     ?  whether  (and  how)  it  will  be  shared  and  preserved  long-­‐term   ?  etc     DMPs  are  o?en  submi?ed  as  part  of  funding  applica?ons,  but  will  be  useful   whenever  researchers  are  crea?ng  (or  reusing)  data,  especially  where  the   research  involves  mul?ple  partners,  countries,  etc…   1d. Roles and responsibilities Who’s involved? It’s worth bearing in mind that RDM is a hybrid activity, involving multiple stakeholder groups… •  The principal investigator (usually ultimately responsible for data) •  Research assistants (may be more involved in day-to-day data management) •  The institution’s funding office (may have a compliance role) •  Library/IT/Legal (The library may issue PIDs, or liaise with an external service who do this, e.g. DataCite.) •  Partners based in other institutions •  Commercial partners •  etc 2. Policies 2a. Data-related policies (UK) •  Seven  “Common  Principles  on  Data  Policy”  –   Data  as  a  public  good;  Preserva?on;  Discovery;   Confiden?ality;  Right  of  first  use;  Recogni?on;   Public  funding  for  RDM   •  Six  of  the  seven  RCUK  funders  require  data   management  plans,  or  equivalent,  at  the   applica?on  stage,  as  do  Wellcome  &  CRUK   •  The  other  council  (EPSRC)  requires  nothing   short  of  an  ins?tu?onal  data  infrastructure  (by   May  2015).  They  also  expect  that  DMP  will  be   a  key  component  of  this…   2b. Data-related policies (USA) • The National Science Foundation (NSF) announced a DMP requirement in 2010, taking effect early in 2011 • White House Office of Science and Technology Policy requirement for DMPs announced March 2013 (programmes awarding >$100m annually) • White House requirements include mechanisms covering compliance with plans and policies, and also cover costs of implementing plans 2c. Data-related policies (Australia) The Australian Research Council (ARC) this year released new instructions for applications for Laureate Fellowships ( http://www.arc.gov.au/ncgp/laureate/ fl_instructions.htm) and Discovery Grants ( http://www.arc.gov.au/ncgp/dp/dp_instructions.htm) Both include the following requirements when describing a proposal… ?  COMMUNICATION OF RESULTS: Outline plans for communicating the research results to other researchers and the broader community, including scholarly and public communication and dissemination ?  MANAGEMENT OF DATA: Outline plans for the management of data produced as a result of the proposed research, including but not limited to storage, access and re-use arrangements 3. DMP in Europe 3a. DMP in Europe: overview •  Horizon 2020 includes a data management (planning) pilot •  http://ec.europa.eu/research/participants/data/ref/ h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data- mgt_en.pdf •  Proposals covered •  “Innovation actions” and “Research and innovation actions” •  DMP contents •  Data types; Standards used; Sharing/making available; Curation and preservation •  Multi phase approach •  Initial DMP due within first 6 months •  Mid-term DMP •  Final review stage DMP •  There are opt-out conditions. A detailed description and scope of the Open Research Data Pilot requirements is provided on the Participants’ Portal 3b. The Horizon 2020 DMP pilot v1: Within Six Months For each data set specify the following: •  Data set reference and name •  Data set description •  Standards and metadata •  Data sharing •  Archiving and preservation (including storage and backup) .docx output from DMPonline 3b. The Horizon 2020 DMP pilot v2 and v3: Mid-Term and Final Reviews Scientific research data should be easily: 1.  Discoverable •  Are the data and associated software produced and/or used in the project discoverable (and readily located), identifiable by means of a standard identification mechanism (e.g. Digital Object Identifier)? 2.  Accessible •  Are the data and associated software produced and/or used in the project accessible and in what modalities, scope, licenses? 3.  Assessable and intelligible •  Are the data and associated software produced and/or used in the project assessable for and intelligible to third parties in contexts such as scientific scrutiny and peer review? 4.  Usable beyond the original purpose for which it was collected •  Are the data and associated software produced and/or used in the project useable by third parties even long time after the collection of the data? 5.  Interoperable to specific quality standards •  Are the data and associated software produced and/or used in the project interoperable allowing data exchange between researchers, institutions, organisations, countries, etc? 4. Support and resources 4a. DCC resources •  Book chapter •  Donnelly, M. (2012) “Data Management Plans and Planning”, in Pryor (ed.) Managing Research Data, London: Facet •  Guidance, e.g. “How-To Develop a Data Management and Sharing Plan” •  DCC Checklist for a Data Management Plan: http://www.dcc.ac.uk/resources/data- management-plans/checklist •  Links to all DCC DMP resources via http://www.dcc.ac.uk/resources/data- management-plans •  DMPonline: https://dmponline.dcc.ac.uk/ • Helps  researchers  write  DMPs   • Provides  funder  ques?ons  and  guidance   •  Includes  a  template  DMP  for  Horizon  2020   • Provides  help  from  universi?es   • Examples  and  suggested  answers   • Free  to  use   • Mature  (v1  launched  April  2010)   • Code  is  Open  Source  (on  GitHub)   h?ps://dmponline.dcc.ac.uk       DMPonline:  overview   Registra?on   Sign  up  with  your   email  address,   organisa?on  and   password     Select  ‘other   organisa?on’  if   yours  is  not  listed   Crea㴮g  a  plan   Select  funder  (if  any)     Select  organisa?on  for   addi?onal  ques?ons   and  guidance     Select  other  sources   of  guidance   Plan  details:  summary   Summary  of  the  sec?ons  and   ques?ons  in  your  DMP   Answering  ques?ons   Notes  who  has  answered  the   ques?on  and  when       Progress  bar  updates  how   many  ques?ons  remain   Sharing  plans   Allow  colleagues  to   read-­‐only,  read-­‐write,   or  become  co-­‐owners   Co-­‐wri㴮g  DMPs   Sec?ons  are  locked  for  edi?ng   when  they’re  being  worked  on   by  colleagues   Expor?ng  DMPs     Can  export  as  plain  text,  docx,  PDF,  html...     Ins?tu?ons  can  customise  the  tool  by…   •  Adding  templates     •  Adding  custom  guidance   •  Providing  example  or  suggested  answers   •  Monitoring  usage  within  their  organisa?on   •  Offering  non-­‐English  language  versions     www.dcc.ac.uk/news/customising-­‐dmponline-­‐admin-­‐ interface-­‐launches     More  informa?on   Customising  DMPonline   www.dcc.ac.uk/news/customising-­‐ dmponline-­‐admin-­‐interface-­‐launches     h?p://www.screenr.com/PJHN     Get  the  code,  amend  it,  run  a  local  instance,  flag  issues,  request  features...   h?ps://github.com/DigitalCura?onCentre/DMPonline_v4     4b. Non-DCC tools and resources •  Book chapter •  Sallans, A. and Lake, S. (2014) “Data Management Assessment and Planning Tools”, in Ray (ed.) Research Data Management, Purdue University Press •  DMPTool •  UKDA guidance •  NERC guidance •  European Union resources •  Resources from other universities, e.g. Oxford (http://researchdata.ox.ac.uk/) 4c. Examples •  There are lots of data management plans available on the Web. The DCC provides links to a number of DMPs via http://www.dcc.ac.uk/resources/data-management- plans/guidance-examples •  Remember that there is no magic bullet, and no one- size-fits-all solution! •  Much of the benefit of data management planning lies in the process of planning, over and above the plans produced at the end of the process •  DMP is a communication activity, between the data collectors and their contemporaries (project partners and funders) and with future data re-users THANK YOU Martin Donnelly Digital Curation Centre University of Edinburgh martin.donnelly@ed.ac.uk Twitter: @mkdDCC www.dcc.ac.uk www.fosteropenscience.eu Image credits: slides 3 and 6, https://www.flickr.com/photos/jayd/; slide 9, https://www.flickr.com/photos/junglearctic/; slide 17, https://twitter.com/AFC_Fisher/