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FAIRness Assessment of the Library of Integrated Network-based Cellular Signatures (LINCS) Resources

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FAIRness Assessment of the Library of Integrated Network-based Cellular Signatures (LINCS) Resources

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The FAIR Guiding Principles facilitate the Findability, Accessibility, Interoperability, and Reusability of digital resources. The Library of Integrated Network-based Cellular Signatures (LINCS) Project has sought to implement the FAIR principles in the provision of its resources in order to optimize usability. We have surveyed the FAIR principles and are implementing specific facets within the LINCS resources. Subsequently, with reference to the literature and other efforts to measure FAIRness, we are developing quantitative metrics to assess the FAIRness of each dataset and resource in order to provide users with objective measures of the characteristics of the LINCS project. Assessing and improving the FAIRness of LINCS is an ongoing effort by our team that will benefit from community input to ensure that all LINCS users are optimally engaged with this resource.

The FAIR Guiding Principles facilitate the Findability, Accessibility, Interoperability, and Reusability of digital resources. The Library of Integrated Network-based Cellular Signatures (LINCS) Project has sought to implement the FAIR principles in the provision of its resources in order to optimize usability. We have surveyed the FAIR principles and are implementing specific facets within the LINCS resources. Subsequently, with reference to the literature and other efforts to measure FAIRness, we are developing quantitative metrics to assess the FAIRness of each dataset and resource in order to provide users with objective measures of the characteristics of the LINCS project. Assessing and improving the FAIRness of LINCS is an ongoing effort by our team that will benefit from community input to ensure that all LINCS users are optimally engaged with this resource.

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FAIRness Assessment of the Library of Integrated Network-based Cellular Signatures (LINCS) Resources

  1. 1. Implementing the FAIR Principles in the Library of Integrated Network-based Cellular Signatures (LINCS) Resources Kathleen Jagodnik, Ph.D. Ma’ayan Laboratory Department of Pharmacological Sciences Icahn School of Medicine at Mount Sinai New York, New York BD2K FAIRness Metrics Working Group June 13, 2017
  2. 2. Overview of the LINCS Project
  3. 3. Overview of the LINCS Project Source: Avi Ma’ayan, PhD
  4. 4. Overview of the LINCS Project Source: Avi Ma’ayan, PhD
  5. 5. Overview of the LINCS Project Source: Vasileios Stathias KINOMEscan P100 Assay MEMA Integration of Data Biochemical KiNativ Proteomic SWATH-MS Transcriptomic RNA-seq L1000 Imaging Fluorescence Microscopy Epigenomic ATAC-seq Global Chromatin Profiling
  6. 6. Overview of the LINCS Project
  7. 7. Overview of the LINCS Project
  8. 8. FAIRness Principles Wilkinson MD et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3: 160018.
  9. 9. Starr, J., Castro, E., Crosas, M., Dumontier, M., Downs, R. R., Duerr, R., ... & Clark, T. (2015). Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Computer Science, 1, e1.
  10. 10. Composite Findability Criteria for LINCS
  11. 11. Composite Accessibility Criteria for LINCS
  12. 12. Composite Interoperability Criteria for LINCS
  13. 13. Composite Reusability Criteria for LINCS
  14. 14. FAIRness Guidelines Wilkinson MD et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3: 160018.
  15. 15. Assessing FAIRness of LINCS Resources Wilkinson MD et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3: 160018. LINCS Resources
  16. 16. Workflows for Assessing LINCS FAIRness Reusability Metric R1: meta(data) are richly described with a plurality of accurate and relevant attributes Sub-Metric R1.1: (meta)data are released with a clear and accessible data usage license
  17. 17. Findability of LINCS Resources
  18. 18. LINCS Metadata Completeness
  19. 19.  6 participants  3 hours  Discussed a range of open questions related to LINCS FAIRness  Produced a Jupyter Notebook that reports statistics for domains associated with first-page Google search results for specified queries DCIC Data Science Symposium Hackathon
  20. 20. Jupyter Notebook for Assessing Google Search Results Query Phrases: LDP NPC methotrexate dataset Valproic Acid dataset MCF7 cells Cancer cell line chemical perturbation dataset Imatinib perturbation dataset Radicolol cell perturbation signature NPC perturbation Methotrexate genes MCF7 MCF7 RNAseq MCF7 L1000
  21. 21. Assessment of Google Search Results
  22. 22. Assessment of Google Search Results
  23. 23. Assessment of Google Search Results
  24. 24. Assessment of Google Search Results
  25. 25. Assessment of Google Search Results
  26. 26. The Problem of Disambiguation LINCS LDS-1299 https://www.lds.org/ http://lincsportal.ccs.miami.edu/ datasets/#/view/LDS-1299
  27. 27. Accessibility of LINCS Resources
  28. 28. The LINCS Data Portal
  29. 29. The LINCS Data Portal
  30. 30. Recommended Content for Landing Pages Starr, J., Castro, E., Crosas, M., Dumontier, M., Downs, R. R., Duerr, R., ... & Clark, T. (2015). Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Computer Science, 1, e1.
  31. 31. Interoperability of LINCS Resources
  32. 32. LINCS Metadata Standards http://www.lincsproject.org/LINCS/data/standards
  33. 33. LINCS Metadata Standards http://www.lincsproject.org/LINCS/data/standards
  34. 34. LINCS Metadata Standards http://www.lincsproject.org/LINCS/data/standards
  35. 35. LINCS Metadata Standards on BioSharing.org
  36. 36. Manual Curation of Metadata
  37. 37. The smartAPI Project smartAPI Specification https://websmartapi.github.io/smartapi_specification/
  38. 38. The smartAPI Project smartAPI Specification https://websmartapi.github.io/smartapi_specification/ 54 API metadata elements, 21 unique to smartAPI
  39. 39. The smartAPI Project smartAPI Editor http://smart-api.info/editor/#/
  40. 40. The smartAPI Project smartAPI Registry http://smart-api.info/registry/
  41. 41. BD2K API Interoperability Working Group Co-chairs: Chunlei Wu Michel Dumontier cwu@scripps.edu michel.dumontier@maastrictuniversity.nl Administrators: Sam Moore Denise Luna samuel.moore@nih.gov deniseluna@bd2kccc.org
  42. 42. Reusability of LINCS Resources
  43. 43. LINCS Data Release Policy http://www.lincsproject.org/LINCS/data/release-policy
  44. 44. LINCS Data Release Policy http://www.lincsproject.org/LINCS/data/release-policy
  45. 45. LINCS Data Release Policy http://www.lincsproject.org/LINCS/data/release-policy
  46. 46. LINCS Versioning Specifications
  47. 47. Mechanism for User Feedback
  48. 48. Mechanism for User Feedback
  49. 49.  Assessed 10 biomedical projects’ licensing info  Sites do not tend to differentiate between data and software  Policies differ widely by resource  Some resources have copyrights, and others don't ~ Some, such as FlyBase, have different copyrights that apply to subsets of resources  Some allow unrestricted use for non-commercial purposes, and require a license for commercial use.  “As-is” disclaimers on some sites  Privacy policies sometimes available; option to opt out  Login typically not required; use of cookies Licensing Survey
  50. 50. 1. The repository has an explicit mission to provide access to and preserve data in its domain. 2. The repository maintains all applicable licenses covering data access and use and monitors compliance. 3. The repository has a continuity plan to ensure ongoing access to and preservation of its holdings. 4. The repository ensures, to the extent possible, that data are created, curated, accessed, and used in compliance with disciplinary and ethical norms. 5. The repository has adequate funding and sufficient numbers of qualified staff managed through a clear system of governance to effectively carry out the mission. 6. The repository adopts mechanism(s) to secure ongoing expert guidance and feedback (either in-house, or external, including scientific guidance, if relevant). 7. The repository guarantees the integrity and authenticity of the data. 8. The repository accepts data and metadata based on defined criteria to ensure relevance and understandability for data users. The Core Trustworthy Data Repository Requirements https://www.datasealofapproval.org/en/information/requirements/
  51. 51. 9. The repository applies documented processes and procedures in managing archival storage of the data. 10. The repository assumes responsibility for long-term preservation and manages this function in a planned and documented way. 11. The repository has appropriate expertise to address technical data and metadata quality and ensures that sufficient information is available for end users to make quality-related evaluations. 12. Archiving takes place according to defined workflows from ingest to dissemination. 13. The repository enables users to discover the data and refer to them in a persistent way through proper citation. 14. The repository enables reuse of the data over time, ensuring that appropriate metadata are available to support the understanding and use of the data. 15. The repository functions on well-supported operating systems and other core infrastructural software and is using hardware and software technologies appropriate to the services it provides to its Designated Community. 16. The technical infrastructure of the repository provides for protection of the facility and its data, products, services, and users. The Core Trustworthy Data Repository Requirements https://www.datasealofapproval.org/en/information/requirements/
  52. 52.  Beyond addressing repositories, develop standards for datasets & tools  Lists of 25 binary criteria for separately evaluating LINCS datasets & tools  Criteria will be updated annually  Open-source Web-based system  Self-evaluation or independent third-party assessment are possibilities Developing New Standards for Datasets & Tools
  53. 53. Proposed Criteria for Dataset Assessment
  54. 54. Proposed Criteria for Tool Assessment
  55. 55. Distribution of FAIR Principles across Criteria
  56. 56. FAIRness Assessment for Example LINCS Dataset Key: Blue: Criterion is satisfied Red: Criterion is not satisfied Black: More info is required to reach a conclusion
  57. 57. FAIRness Assessment for Example LINCS Dataset The dataset is available in a human-readable format
  58. 58. FAIRness Assessment for Example LINCS Dataset
  59. 59. FAIRness Assessment for Example LINCS Tool Key: Blue: Criterion is satisfied Red: Criterion is not satisfied Black: More info is required to reach a conclusion
  60. 60. FAIRness Assessment for Example LINCS Tool All previous versions of the tool are made available
  61. 61. FAIRness Assessment for Example LINCS Tool
  62. 62. Challenges in Assessing LINCS FAIRness ?
  63. 63. LINCS FAIRness Assessment
  64. 64. Summary of Interim Results
  65. 65.  How to assess the quality of information in an automated manner?  How to clearly differentiate among FAIRness criteria and sub-criteria ~ Will this differ by project?  Do certain criteria precede others? Open Questions
  66. 66. Open Questions
  67. 67. Future Work
  68. 68. Acknowledgments  Stephan Schurer, Ph.D.  Dusica Vidovic, Ph.D.  Daniel Cooper, Ph.D.  Raymond Terryn, Ph.D.  Caty Chung, M.S.  Vasileios Stathias, B.S.  Ajay Pillai, Ph.D.  Avi Ma’ayan, Ph.D. NIH T32 Training Grant #4T32HL007824-19  Denis Torre, B.S.  Alexandra Keenan, M.S.  Wen Niu, M.S.
  69. 69. References  Dunning A., de Smaele M., Bohmer J. (2017) Are the FAIR Data Principles fair? IDCC17 Practice Paper. The 12th International Digital Curation Conference, February 20-23, 2017, Edinburgh, Scotland.  FORCE 11 (2014a). The FAIR Data Principles. FORCE11. Retrieved 18 January 2017, from https://www.force11.org/group/fairgroup/fairprinciples  FORCE 11 (2014b). Guiding Principles for Findable, Accessible, Interoperable and Re-usable Data Publishing version b1.0. FORCE11. Retrieved 18 January 2017, from https://www.force11.org/fairprinciples  H2020 Guidelines on FAIR Data Management: http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data- mgt_en.pdf  Sansone, S.-A. et al. (2017) DATS: the data tag suite to enable discoverability of datasets. bioRxiv, 103143.  Starr, J. et al. (2015) Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Comp Sci, 1, e1.  Wilkinson, M. D. et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3.  Wilkinson, M. D. et al. (2017) Interoperability and FAIRness through a novel combination of Web technologies (No. e2522v2). PeerJ Preprints.
  70. 70. Images Used  Magnifying glass icon: http://images.clipartpanda.com/magnifying-glass-clipart-biy5E46iL.png  Key icon: https://img.clipartfest.com/7b75f290f4781b7331b6bb477ab7ea69_black-olde-key-clip-art-key-black-and-white-clipart_640-480.svg  Gears icon: https://cdn.shutterstock.com/shutterstock/videos/10879745/thumb/1.jpg  Recycling icon: http://www.recycling.com/wp-content/uploads/recycling%20symbols/black/ Black%20Recycling%20Symbol%20(U+267B).gif  Green pie chart: http://www.psycinsight.co.nz/wp-content/uploads/2015/03/pie-chart-green.jpg  Documentation icon: https://d30y9cdsu7xlg0.cloudfront.net/png/192334-200.png  Missing puzzle pieces: http://www.lshtm.ac.uk/php/departmentofhealthservicesresearchandpolicy/researchareas/economic/ addressingmissingdataincea/puzzle_300.jpg  Vocabulary: http://dev3.ccs.miami.edu:8080/apis/#/datasets  Ontology: https://1.bp.blogspot.com/-gNWHuPpPhDA/T060tS4uk_I/AAAAAAAAqK0/G2Mb69rwMZg/s1600/GO.png  Metadata sphere: https://silwoodtechnology.files.wordpress.com/2013/07/metadata_ball.jpg  Diminishing returns: https://personalexcellence.co/files/graph-diminishing-returns.gif  Documentation: Open book: https://mountainss.files.wordpress.com/2012/09/sysctr-documentation-icon.jpg?w=611  Ontology on blackboard: http://www.emiliosanfilippo.it/wp-content/uploads/2011/11/Ontology.jpg  Data Seal of Approval: http://datasupport.researchdata.nl/uploads/pics/logo_DSA_regulier_120x120_01.jpeg  Diverse users: http://ymedialabs.com/wp-content/uploads/2016/02/target.jpg  Pins in map: https://www.gladd.co.uk/images/images/mystery_location.jpg  Checklist: http://vinciworks.com/blog/wp-content/uploads/2017/03/Data-protection-checklist.png  Bull’s eye of relevance: http://jisushopping.net/B2Bblog/wp-content/uploads/2013/11/JiSu-B2B-Blog-Marketing-Offer-Relevance.jpg  Questions: http://download.4-designer.com/files/20121225/3D-villain-with-a-question-mark-high-quality-pictures-2-34592-thumb.jpg

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