Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Practicing Open Science

79 views

Published on

Digital Repository of Ireland training on Open Science for the Irish Research Council, April 2019

Published in: Education
  • Be the first to comment

  • Be the first to like this

Practicing Open Science

  1. 1. Practicing Open Science Digital Repository of Ireland 11th April 2019
  2. 2. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  3. 3. What is the Digital Repository of Ireland? ● A national data infrastructure ● Humanities, Social Sciences, Arts (research data) ● Long-term digital preservation, access, discovery ● Ireland’s social and cultural record ● Royal Irish Academy, Trinity College Dublin, Maynooth U ● Curated collections; cross-searchable metadata ● Open Access, Open Research ● A certified trusted digital repository (TDR)
  4. 4. Why Practice Open Science?
  5. 5. What is Open Science? ● Science = all disciplines ● Open Science -- Open Research ● ‘Opening’ the practice of research ● Openness = value ● Research process and outputs as widely accessible as possible ● Citizen Science ● Link to Research Integrity
  6. 6. Source: YERUN
  7. 7. Publications Research Data Research Processes OPENNESS
  8. 8. Publications Research Processes OPENNESS Research Data
  9. 9. Why Practice Open Science? Better Research & Value Public funding = public access Fuller picture of research outputs Increased visibility Better ROI Accelerated research Collaboration/exchange Transparency Reproducibility
  10. 10. Risks of not practicing OS Failure to meet funder mandates Decreased exposure Lack of transparency Changes to research culture Next-generation metrics
  11. 11. Where does DRI fit into this? National infrastructure for archiving, preserving, and sharing research data Significant involvement in the emerging policy landscape for Open Science
  12. 12. Research Data Lifecycle
  13. 13. DRI and Open Science Policy European Open Science Cloud
  14. 14. Open Access Publishing
  15. 15. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  16. 16. Open Access publishing Traditional subscription based journals publishing Some OA journals ask for a fee called Article Processing Charge (APC) No fees for publishing 2 Who pays for publishing? Most often use the Creative Commons licenses. Publications can be used for a variety of purposes provided that the users attribute the work to the authors. Copyright is usually transferred to the publisher (the journal). Users need to request permission to use the work in any way. 3 Author rights and how can publications be used? No fees for access Readers / institutions have to pay for access (pay per article or yearly subscriptions) 1 Who pays for use? Understanding Open Access Publishing
  17. 17. Gold Route ● access to publications is immediate and free for anyone to read ● via the Open Access journals (OA native) Open Access publishing is possible through both OA journals and traditional subscription based journals Green Route ● a version of an article or paper published in a subscription based journal is available free of charge in a repository or similar Routes to Open Access
  18. 18. Benefits Open Access The main objective is to maximise accessibility to your publication / increase readership ● Extensive scientific knowledge widely and openly available (vs readers having to pay for access to scientific knowledge) ● Authors can maximise readership and maintain rights to their work (vs authors have a smaller audience and are forced to relinquish the rights associated to their work) ● Open access and re-use allows others to build upon your work and helps avoid duplication
  19. 19. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  20. 20. Identifying Open Access journals Short hands-on exercise: (15min) Identify 2 Open Access publishing journals in your specific discipline using DOAJ https://doaj.org & SHERPA RoMEO http://sherpa.mimas.ac.uk/romeo/ One as an example of the gold route to OA and one as an example of the green route Based on the information available review their publishing policies, costs, use and rights policies
  21. 21. Summary and links Open Access = Free to read + Free to use Open Access publishing is highly recommended and often is an eligible cost to be included in the grant application Resources DOAJ https://doaj.org (Directory of Open Access Journals) SHERPA RoMEO http://sherpa.mimas.ac.uk/romeo/ (Analysis of the publisher Open Access policies)
  22. 22. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  23. 23. Research Data Management
  24. 24. What is Research Data? Research data is the data that is gathered, generated or used as part of the research process
  25. 25. What is Research Data Management? Research Data Management is the term used to refer to the process of organising, storing, using, preserving and sharing Research Data. It is an active process of managing the data that forms the inputs to and outputs of your research, over the lifetime of a research project, and beyond. Research Data Management ensures that you can keep track of, and effectively use your own data, but also that other researchers will have the opportunity to find and use your data to reproduce your results or undertake further research.
  26. 26. The Research Data Lifecycle
  27. 27. RDM Lifecycle: Plan and Create Creating and/or collecting data is not necessarily the beginning of the Research Data Lifecycle. The Research Data Lifecycle actually begins with planning. This planning should take place as early as possible in the research process, and is often required by funders when making a funding application. The plan is called a Data Management Plan and we will look at these in more detail shortly.
  28. 28. RDM Lifecycle: Document, Use and Store When performing research you will be using and creating a lot of Research Data. To make sure that you can effectively use this data you need to think about ● Annotating / documenting the data ● Analysis, versioning of data and results ● Storage and Backup
  29. 29. RDM Lifecycle: Share and Preserve The final stages in the Research Data Lifecycle are to share your data (not just publications) and to ensure the long-term shareability of your data To do this, you must think beyond the short-term storage solutions that you used while performing the research and think about depositing your data in a widely-used Data Repository where it will benefit from FAIR access and long-term preservation
  30. 30. FAIR Data Findable Accessible Interoperable Reusable
  31. 31. Preservation & Sustained Sharing FAIR data is shareable data, but long-term Preservation is required to ensure sustained sharing. It is not enough to back up your data and make it accessible online ● What happens if the website hosting your data is no longer accessible? ● What happens if the file format you used for your data is no longer supported by modern software? ● What happens if the back up files become corrupt and cannot be opened?
  32. 32. Trusted Digital Repositories The Data Life Cycle is a process which continues after your research is complete. A Trusted Digital Repository is a Repository which is certified as trustworthy because it has procedures in place to carry on the Data Life Cycle process for your data.
  33. 33. Trusted Digital Repositories There are two main certification frameworks ● CoreTrustSeal ● ISO 16363
  34. 34. Summary Research data is all of the inputs and outputs to your research as well as the analyses and processes carried out on that data Research Data Management is the process of looking after your data during the Research Data Lifecycle and beyond FAIR Data is Findable, Accessible, Interoperable and Reusable Trusted Digital Repositories can ensure that your data will continue to be managed after your research is complete, and that they will be accessible for the long term
  35. 35. Useful links / Resources FAIRsharing https://fairsharing.org/ A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies. DRI Guide to Research Data: http://dri.ie/research-data-management-plans UCD Library Research Data Management Guide: http://libguides.ucd.ie/data DRI Blog: Why storage is not preservation: https://www.dri.ie/why-storage-not- preservation-conversation-surrounded-conservation Digital Object Identifier (DOI) site https://www.doi.org/ CoreTrustSeal https://www.coretrustseal.org/ ISO 16363 http://www.iso16363.org/
  36. 36. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  37. 37. Data Management Planning
  38. 38. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  39. 39. Guide to Data Management Plans - Steps include: - Organising and documenting your data - Processing your data - Storing your data - Protecting your data Examples: Data Curation Centre step-by-step DMPs
  40. 40. Why Data Management Plans? •Makes data available to support the findings of the research •Provides proper attribution to those who contributed to the creation of the data; •Makes data accessible in a reusable form that will facilitate secondary usage; •Helps store data securely during the active phase of the research project; •Helps preserve data in the long-term when the project has ended; •Is compliant with the requirements of research funders
  41. 41. Steps of a DMP •Organising and documenting data - Consistent file naming - Non-proprietary formats - Project documentation e.g. research questions, methodologies - Metadata - descriptive, technical etc
  42. 42. Steps of a DMP •Processing data - Consistent versioning of files, existence of a ‘master file’ - Interoperability e.g. assigning unique identifiers, supporting citation
  43. 43. Steps of a DMP •Storing data - Storage and backups - 3 locations rule - Costing storage e.g. cost of external drives or institutional storage - Scheduled backups - Security - anonymisation when needed, clarity in restricted data agreements
  44. 44. Steps of a DMP •Protecting data - Liaising with institution ethics offices - Informed consent in advance of fieldwork - Agreements for ethical use and reuse - Clarity in intellectual property rights / copyright
  45. 45. Steps of a DMP •Preserving data - Planning for storage and access after project ends - Appraisal of what needs to be kept and what should be destroyed - Making sure repository has PIDs - Awareness of any data embargoes (e.g. social science data) - Levels of access to data
  46. 46. How to make a DMP Templates are the easiest way to create a DMP Digital Curation Centre has several downloadable templates as part of their DMPonline tool. Anyone can set up an account and practice. Link and walkthrough https://dmponline.dcc.ac.uk/ https://dmponline.dcc.ac.uk/plans/new
  47. 47. Useful links Guide to using DCC DMPonline tool: http://libguides.ucd.ie/ld.php?content_id=31601339 Research Data and DRI: http://dri.ie/research-data-management-plans UCD Research Data Management Portal https://libguides.ucd.ie/data University of Edinburgh Research Data Support Service: https://www.ed.ac.uk/information-services/research-support/research-data-service
  48. 48. Metadata
  49. 49. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  50. 50. Metadata is data about data It can take many forms: Descriptive, structural, technical, administrative, use Equally as important as what you collect, is when you collect
  51. 51. Metadata collection starts with data creation
  52. 52. Image courtesy of the University of Virginia Library.
  53. 53. What do you need to collect? ● Metadata is the structured information that allows you to find, retrieve and re-use another resource (the dataset) ● At a minimum you need to record who created the dataset, when it was created or published, and give it title or descriptive name ● The formats and notation of your metadata will vary based on your discipline, but it will usually fall into particular categories.
  54. 54. Categories of Metadata ● Descriptive: describes the intellectual content of the resource, through an accepted standard e.g. Dublin Core ● Structural: Provides information about the internal structure of the dataset ● Technical: information about filetypes, software and hardware which render a digital object ● Administrative: manages property rights, version control and alteration of the data and metadata itself ● Use metadata: manages access controls and licenses, determines re-usability ● Preservation: documents actions undertaken to preserve a resource
  55. 55. Categories of Metadata ● Descriptive: describes the intellectual content of the resource, through an accepted standard e.g. Dublin Core ● Structural: Provides information about the internal structure of the dataset ● Technical: information about filetypes, software and hardware which render a digital object ● Administrative: manages property rights, version control and alteration of the data and metadata itself ● Use metadata: manages access controls and licenses, determines re-usability ● Preservation: documents actions undertaken to preserve a resource
  56. 56. Categories of Metadata ● Descriptive: describes the intellectual content of the resource, through an accepted standard e.g. Dublin Core ● Structural: Provides information about the internal structure of the dataset ● Technical: information about filetypes, software and hardware which render a digital object ● Administrative: manages property rights, version control and alteration of the data and metadata itself ● Use metadata: manages access controls and licenses, determines re-usability ● Preservation: documents actions undertaken to preserve a resource
  57. 57. Overview of Metadata Standards ● Standards help you record the correct information for your discipline ● Use of standards encourages consistency of documentation for similar datasets ● This facilitates greater findability and interoperability
  58. 58. Overview of Metadata Standards Metadata standard resources online: https://rdamsc.bath.ac.uk/ http://www.dcc.ac.uk/resources/metadata-standards/list https://www.ddialliance.org/
  59. 59. Metadata Example: Dublin Core
  60. 60. Metadata Example: Dublin Core
  61. 61. Metadata Example: Dublin Core For DMP purposes this can be recorded in a spreadsheet format - something like this https://docs.google.com/spreadsheets/d/1MG43uAfwXeIizoZj6KiLuMquZJeCu yzV0YsW8CZgM8I/edit?usp=sharing
  62. 62. You don’t need to know how to code!
  63. 63. Summary ● Metadata is essential to accurately describe, find and retrieve your dataset ● Collection of rich metadata will enhance interoperability, findability and access. ● Metadata types vary, but standards are available ● Always a good idea to focus on descriptive and provenance metadata
  64. 64. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  65. 65. Exercise - Exercise: identifying RD in participants’ domains, reflect on data, how can it be categorised and preserved (15mins) - Link to worksheet
  66. 66. Open Science
  67. 67. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions
  68. 68. Publications Research Data Research Processes OPENNESS
  69. 69. Open Research Processes The goal is to make the entire research project open and available This makes it easy for other researchers to understand exactly how we derived our results, to verify them and to build on our work Open Research processes should include the project plans, experimental protocols, software and tools, analysis workflows, raw data, intermediate results and all other relevant components of a research project
  70. 70. Open Notebook Science Open Notebook Science replaces the traditional lab notebook with an open version in which each experiment is recorded as it happens Open Notebook tools allow the data, protocols, results and other associated components of each experiment that makes up a research project to be published Facilitates citation of exact experiments, reproducibility, evaluation, teaching, public confidence and trust... Example: http://bit.ly/2D7tF4W
  71. 71. Workflow Engines A Workflow Engine is a tool that allows a researcher to design and execute workflows by integrating many different software components Workflow tools come with a variety of components for common computations and provide access to scientific databases They often integrate with distributed research e-Infrastructures such as the European Open Science Cloud Workflow engines allow the same analyses to be rerun on different datasets, as well as shared with other researchers Example: http://bit.ly/2Z2ANJa
  72. 72. Useful Links and Resources Science Gateways https://sciencegateways.org/ CrowdSourcing https://www.zooniverse.org/ https://www.scistarter.org/ Workflows https://www.myexperiment.org/ https://taverna.incubator.apache.org/ Open Data Repositories https://figshare.com/ https://zenodo.org/ Open Notebooks http://onsnetwork.org/ https://theolb.readthedocs.io/en/latest/ Open-Source Software https://github.com/ https://about.gitlab.com/
  73. 73. Agenda 2:00pm Why Practice Open Science? 2:15pm Understanding Open Access publishing 2:30pm Exercise: Identifying Open Access journals 2:45pm Managing and Sharing your Research Data 3:00pm Comfort break 3:05pm Data Management Planning 3:20pm Metadata and Access 3:30pm Exercise: Identifying your Research Data 3:45pm Tools 3:50pm Questions

×