DATA MANAGEMENT PLAN

Transcription

1 DATA MANAGEMENT PLAN The framework to meet CHONe funding requirements By Michelle Lloyd, Kate Crosby, Peter Lawton Data Management Team Canadian Healthy Oceans Network November 2013 Approved and endorsed by Canadian Healthy Oceans Network Scientific Advisory Committee (SAC) and Board of Directors Copyright by Canadian Healthy Oceans Network,

2 TABLE OF CONTENTS Data Management Plan Research Documentation Researcher Information Research Description Discovery Metadata Research Discovery Data Reports Interactive Map Discovery Database Metadata Submission Private Data Repository for CHONe Researchers only Data Submission Data Record Metadata Record Documentation Additional Resources Data Sharing and Preservation Timeline References Additional Resources Glossary

3 DATA MANAGEMENT PLAN The data management plan has been developed to meet the data management mandate, which is to ensure all data will be freely available by March 2014 (or 2 years after completion of data collection, whichever comes last), and to ensure long-term preservation and accessibility of data. The workflow (Figure 1) consists of 5 Steps: Step 1: Focus on compiling researcher information, research descriptions and discovery metadata. Step 2: Create a Discovery Database and products for metadata exploration, using the research documentation from Step 1. Step 3: Establish a private CHONeData Repository for researchers to store and share research data. Step 4: Focus on compiling data packages required for preservation and permanent archival of research data. Step 5: Focus on preservation and archival of data packages in permanent Public Data Repositories that will enable reuse. While research projects or subprojects are underway we anticipate that information (data and metadata) will be modified on various schedules. As portions of each research project are published, either as a data package or a scientific article, there will be specific completion points after which component documentation will no longer require editing by the researcher. At the full completion of the project or subproject then it may be expected that the information will be considered a final record of the research undertaken. At that point, unless the above steps have been completed, it will not be easy for others to assess and reuse the information. 2

4 Figure 1. CHONe Data Management Workflow. The workflow outlines the research documentation (i.e. researcher information, research description and discovery metadata) required for the Discovery Database and products, the CHONe Data Repository and data package required for preservation of CHONe data and permanent public archival and reuse. 1. Research Documentation 1.1 Researcher Information All researchers (e.g. investigators, students and postdocs) must update or provide their researcher information. Basically, this is the contact information for the researcher. 1 The researcher information includes: a) Researcher Code 1 Researchers can update their researcher information at any time. 3

5 b) First Name c) Last Name d) Role within CHONe e) Affiliation f) Street Address g) Phone Number h) Address Students and postdoctoral fellows must also include the start and end date (or estimated end date) and status of their degree or position, respectively. 1.2 Research Description Project leads and researchers must update or provide their project and subproject research description, respectively. 2 This is the information about their research project or subproject. The research description includes the project or su a) Title (i.e. thesis, thesis chapter, or publication), b) Abstract (i.e. thesis/publication abstract), c) Objectives, d) Keywords, e) Researchers involved, and f) Publications or theses produced. 1.3 Discovery Metadata Project leads and researchers must provide discovery metadata for their projects and subprojects, respectively. 3 The discovery metadata conforms to international metadata standards, ensuring interoperability among multiple users and data systems, and will be used to create a searchable Discovery Database. Discovery metadata and database will facilitate global discoverability, understandability and reusability of data. Complete online discovery metadata survey. 2 Project leads and researchers can update their research descriptions at any time. 3 Project leads and researchers can update their discovery metadata at any time. Investigators will be required to complete the discovery metadata survey on behalf of their students or postdoctoral fellows who do not complete the survey. 4

6 2. Research Discovery From researcher information, research descriptions and discovery metadata, three discovery products (data reports, an interactive map, and a Discovery Database) will be produced by the data management team. These will ensure that CHONe data are discoverable, accessible and reusable for collaborators and stakeholders. Discovery products will be sent to researchers for approval before being made public. The data reports, interactive map, and discovery database will be published online under the Data tab (Figure 2) on the website by the data management team. The data webpage will include a network-level data report, along with links to project and subproject data reports, the interactive map, discovery database, and data management documents (i.e. Data Policy, Introduction to Data Management, Data Management Plan, Appendix and Glossary). Figure 2. Screen shot of the Data webpage, with links to Discovery Database, discovery metadata, CHONe Data Repository Data CHONe website. 2.1 Data Reports Data reports combine researcher information, research descriptions and discovery metadata to provide collaborators and stakeholders (i.e. public) a summary of the research and research data available for CHONe, themes, projects and subprojects. These data reports 4 may contain: About the Research Title 4 Theme leaders, project leads and researchers can update their data reports at any time. 5

7 Data Report Abstract Objective Keywords Researchers involved Data unique ID number (administration only) Data Title Data Description Variables, parameters or attributes Data Citation Status, Start and End (or anticipated end) Date Geographic Coverage o Latitude and Longitude o Geographical Names Temporal Coverage o Year Range o Sampling Dates Taxonomic Coverage o Organism Description o Taxonomic Names Funding Scientific Contacts Date Last Modified Related publications Data Centre Access and Usage See Appendix 2 for data report examples for CHONe, projects and subprojects Interactive Map The interactive map will allow users to visualize discovery metadata using the Google Fusion Tables application. The application will filter the discovery metadata based on the user query, which can be visualized as a map or chart (see Figure 3). 6

8 a) b) Figure 3. An example of potential outputs using Google Fusion Tables. Recorded data from a larval survey was filtered to display (a) sampling locations; (b) spatial information, taxonomic information, and other information for specific sample sites using a map-based query function Discovery Database In order to have a searchable relational database, duplications and/or conflicting use of specific terms must be avoided, relationships between different variables, parameters and attributes must be understood and properly mapped between component database tables, and data providers must understand what searches for commonality/insight among data might drive user queries. Trying to find commonality among the research studies is daunting, and the simplified metadata database framework that has been developed was only possible thanks primarily to student metadata contributions. 7

9 The Discovery Database, based on metadata, is divided into two levels of organization. The first level organization will allow users to search the metadata by who (e.g. researcher), where (e.g. spatial or geographic coverage), and when (e.g. temporal coverage), and what (e.g. data details) categories (Figure 4). The second level, the what category, will allow users to search the metadata by data title, data abstract, taxon, and variables, parameters and attributes (Figure 4). Figure 4. CHONe Discovery Database framework. The first level includes all the metadata about who, what, where and when, whereas the second level includes metadata such as the data title, data abstract, taxonomic names, and variables, parameters and attributes. Some of these variables can be derived from provided variables. For example, geographical name, ocean, ecoregion and bioregion can be derived from latitude and longitude. 8

10 The Discovery Database will also be searchable by research Theme (marine biodiversity, ecosystem function, and population connectivity), project (i.e. by project code) and subproject (i.e. by collection code) (Figure 5). Figure 5. The Discovery Database will be searchable by the organization ofchone. Researchers will be able to search the database by theme, project and subproject Metadata Submission Discovery metadata will be sent by the data management team to the Ocean Biogeographic Information System (OBIS) for CHONe 1.0, as well as to the International Oceanographic Data and Information Exchange (IODE), Integrated Science Data Management (ISDM), etc. for CHONe 2.0 for global discovery of CHONe data. Once the data package is published, a link to the data package will be added to the discovery metadata. 3. Private Data Repository for CHONe Researchers only The CHONe Data Repository is a secure storage location for all CHONe data records, metadata records, documentation, theses, etc. The data repository has ~150 GB of storage space, available through the CHONe website, hosted on the Centre for Marine Biodiversity (CMB) server. Data deposited within the repository will be backed up regularly (every day, minimising the risk of loss), and available to researchers as and when required. 5 5 The Private CHONe Data Repository is for short-term storage of data. The data will be stored within the repository, as long as CHONe funds remain to maintain it. 9

11 Access to the CHONe Data Repository is restricted to researchers only. Researchers must login with their login name and password (Figure 6) to be able to access this repository, which is located under the D CHONe website (Figure 2). Within the repository researchers have access to folders, which are organized by theme, project, and subproject. Specific access restrictions (ie only available to a defined sub-set of researchers), and/or embargos may be applied to any folder or file, if requested. Figure 6. Login using researcher ID (all lowercase) and password to be able to access the Data Repository. First time users MUST contact Susan Curtis, Administration Officer to obtain a temporary password. Once you have logged in, change your password. 4. Data Submission Researchers must upload their CHONe related data packages (i.e. data record, metadata record and documentation) to the CHONe Data Repository. If your research data is already archived in a publicly accessible data repository, provide the data management team with a link to and location of your data. Researchers are strongly encouraged records immediately after collection, as well as their latest version (or modified) data records to ensure data is protected against accidental loss. Data record metadata and the necessary documentation needed should be uploaded upon the completion of data collection or before research completion Data Record The data record is a collection of data. Usually, it is the contents of a single database table, where each column of the table represents a particular variable, and each row corresponds to a given member of the data record in question. 4.2 Metadata Record 10

12 The metadata record is the detailed information about the specific subproject (or project, if another researcher to understand a moderately complicated data record after reviewing the metadata record for 20 minutes. In the case of metadata, providing more information is better. All data records (from projects, subprojects, theses, chapters or publications) should have a corresponding metadata record to allow understanding of the nature and limitations of the data for users. A metadata record is also required for submission of a data record to a Public Data Repository for archival, preservation and reuse. See Appendix 3 for an example. 4.3 Documentation Data record documentation refers to any documents that will help make your data re-useable and understandable to another user for their purposes. The documentation usually addresses the following types of questions: 1. What did the original study set out to do? 2. How the research contributes new knowledge to the field? 3. What were the research questions/hypotheses tested? 4. What methodologies were used? 5. What sampling techniques or designs were used? 6. What instruments, and specific measurements were made? 7. How was the sampling organized? 8. How were different variables, attributes or parameters in the data record defined and created? 9. What was done with missing data? 10. knows? 4.4 Additional Resources MANTRA a Research Data Management Training course provides online data management tutorials and resources designed for graduate students and others Data Sharing and Preservation 6 Should CHONe be renewed, a data management workshop (and webinars) will be held for researchers early on and throughout their research projects and subprojects. 11

13 All CHONe research data 7 must be publically available fully and, and must be preserved and accessible for long-term reuse to meet the s data management requirements. Data packages will be permanently archived within Public Data Repositories (such as GenBank, DataONE, DRYAD, figshare, etc) for long-term data preservation, accessibility, discovery and reuse. These permanently, publicly available data packages are citable. 8 In addition, all marine species metadata (or data record subsets) will be permanently archived within the Ocean Biogeographic Information System for additional discovery and reuse. TIMELINE Tasks Completion Date: Completed By: Hire Data Management Coordinator February 2013 Joan Atkinson and Peter Lawton (>50%). June 7, 2013 Data Management Coordinator Hire Data Manager June 10, 2013 Joan Atkinson and Peter Lawton Upgrade CMB server July 1, 2013 Contractor Data Policy and Data Management Plan sent to Theme Leaders for comments July 5, 2013 Peter Lawton and Michelle Lloyd Review Data Policy and Data Management Plan, provide comments to Data Management Team July 26, 2013 Theme Leaders Revise Discovery Metadata survey, send out to several researchers to test October 1, 2013 Kate Crosby 7 CHONe research data includes any and all research data collected and generated by CHONe researchers and collaborators, and CHONe funded projects during the CHONe time frame, from Canadian Institute of Health Research (CIHR) funded researchers are required to ensure that all research papers generated from CIHR funded projects are freely accessible through the Publisher's website or an online repository within 12 months of publication. Also, NSERC Discovery Grants consider cost associated with publishing data packages, an eligible expense. 12

14 Revise Data Policy and Data Management Plan, send to Paul Snelgrove and Theme leaders October 1, 2013 Michelle Lloyd and Peter Lawton Review Data Policy and Data Management Plan, provide Data Management Team with final comments, and to endorse documents October 21, 2013 Paul Snelgrove and Theme Leaders Revise Data Policy and Data Management Plan, and seek approval from SAC and Board of Directors December 1, 2013 Michelle Lloyd and Peter Lawton Send Discovery Metadata survey to researchers December 15, 2013 Data Management Team Complete Discovery Metadata survey and update Research Descriptions for Projects and Subprojects January 9, 2013 Project leads, Researchers 9 Create Data Repository October 1, 2013 Data Management Team Create data reports January 31, 2014 Data Management Team Create Discovery Database and interactive map January 31, 2014 Kate Crosby Data reports approved by researchers before published online. February 14, 2014 Project leads, Researchers 10 Data packages for corresponding published articles, deposited into a permanent public data repository Data management team to work with researchers to create Record Metadata and Documentations for data records. 11 March 1, 2014 Researchers 10 October 1, 2013 until June 31, Data Management Team, Researchers 9 Students and postdoctoral fellows must have an investigator approve their survey and research description. 10 Researchers must consult with all co-authors. 11 Only for projects and subprojects, that have completed data collection 12 June 31, 2014 end of CHONe 13

15 Data Management Team to have a copy of all CHONe Data March 1, 2014 Researchers Subset of the metadata will be sent to OBIS June 31, 2014 Data Management Team and Researchers REFERENCES Canadian Healthy Oceans Network Research Agreement. Canadian Healthy Oceans Network, Updated January 22, Canadian Healthy Oceans Network Deliverables Report. Canadian Healthy Oceans Network, Reichman OJ, Jones MB, Schildhauer (2011) Challenges and opportunities of open data in ecology. Science 331, 703. doi: /science Wallis JC, Rolando E, Borgman CL (2013) If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology. (L. A. Nunes Amaral, Ed.)PLoS ONE, 8(7), e doi: /journal.pone Whitlock MC, McPeek MA, Rausher MD, Rieseberg L, Moore AJ (2010) Data Archiving. American Naturalist. 175(2): , ADDITIONAL RESOURCES Baker, C. S Journal of Heredity Adopts Joint Data Archiving Policy. Journal of Heredity. 104(1):1, Butlin, R Data archiving. Heredity advance online publication. 28 April. Fairbairn, D. J The advent of mandatory data archiving. Evolution. 14

16 Moore, A. J., M. A. McPeek, M. D. Rausher, L. Rieseberg, and M. C. Whitlock The need for archiving data in evolutionary biology. Journal of Evolutionary Biology. Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE 2(3): e308. doi: /journal.pone Research Data MANTRA [online course] by EDINA and Data Library, University of Edinburgh Rausher, M. D., M. A. McPeek, A. J. Moore, L. Rieseberg, and M. C. Whitlock Data Archiving. Evolution. Rieseberg, L., T. Vines, and N. Kane Editorial and retrospective Molecular Ecology. 19(1):1-22, Stephanie E Hampton, Carly A Strasser, Joshua J Tewksbury, Wendy K Gram, Amber E Budden, Archer L Batcheller, Clifford S Duke, and John H Porter Big data and the future of ecology. Frontiers in Ecology and the Environment 11: Tseng, M. and L. Bernatchez Editorial: 2009 in review. Evolutionary Applications. 3(2):93-95, Uyenoyama, M. K MBE editor's report. Molecular Biology and Evolution. 27(3): Wenburg, J. K Data Archiving. Journal of Fish and Wildlife Management. GLOSSARY This glossary (still a work in progress) is intended to provide common terms for use across documents and online resources relating to CHONe data management. Collection Code is a unique code for each subproject (or project if no subproject exists). The code is a compilation of the network, project and subproject code and in some cases includes a subproject identifier (e.g. CHONe_PC-06_LLOYDM or CHONe_PC-06_DAIGLER_a). 15

17 Data are any or all values of qualitative or quantitative variables (i.e. attributes), belonging to a set of items, collected in performance of CHONe research (Research Agreement, Section 2). Also see raw data, processed data, and research data Data Authorship is generally attributed to the individual(s) that made substantial contribution to the collection of research data. DataONE (i.e. Data Observation Network for Earth) is a collaboration among many partner organizations, and is funded by the US National Science Foundation (NSF) under a Cooperative Agreement. Data Ownership (i.e. who owns the data?) belongs to the researcher, but ultimate ownership belongs to the institution. Researchers can make copies for their own and personal use. In industry, ownership is defined by the contract; data usually belong to the company and in government as well. In academia, the ownership is defined as the university, although the university rarely asserts their ownership over researchers. Data Package is the folder containing the data record, metadata record and relevant documentation. Data Record (i.e. Dataset) is a collection of data. For example, a data record is the contents of a single flat database table where each column of the table represents a particular variable, and each row corresponds to a given member of the data record in question Data Reports combine Researcher Information, Research Descriptions and Discovery Metadata to provide collaborators and stakeholders (i.e. public), a summary of the research and research data for CHONe, themes, projects and subprojects (e.g. theses, thesis chapters or publications) Data Rescue includes the identification and recovery of data considered to be at risk (i.e. files stored on personal computer, lab computers, external hard drives etc. This is closely related to Archives, but because of the aging of science staff and staff reductions, it is singled out for special attention. Discovery Database (i.e. CHONe Discovery Database) is searchable CHONe database created from CHONe discovery metadata, instead of data records or metadata records. 16

18 Discovery Metadata (i.e. CHONe Discovery Metadata) is structured information that describes what, where, when of the CHONe research data, by who and how it was collected, and who funded it. Documentation (i.e. data record documentation) consist of mental notes, hand-written notes, field/lab notebook, comments field in excel, proposal, thesis, thesis chapters, publications, note or code books, methods, etc. Basically any documents that will help make your CHONe data record re-useable. DRYAD (i.e. DRYAD Digital Repository) is a curated resource that makes the data underlying scientific publications discoverable, freely reusable, and citable. Dryad provides a generalpurpose home for a wide diversity of data types. Figshare is a repository where users can make all of their research outputs available in a citable, shareable and discoverable manner. Figshare allows users to upload in many file formats that can be viewed in the browser, so that figures, data records, media, papers, posters, presentations and files can be disseminated in a way that the current scholarly publishing model does not allow. GBIF (i.e. Global Biodiversity Information Facility) was established to encourage free and open access to biodiversity data, via the Internet. Through a global network of countries and organizations, GBIF promotes and facilitates the mobilization, access, discovery and use of information about the occurrence of organisms over time and across the planet. GenBank is the National Institute of Health (NIH) genetic sequence database, an annotated collection of all publicly available DNA sequences. GenBank is part of the International Nucleotide Sequence Database Collaboration, which comprises the DNA DataBank of Japan (DDBJ), the European Molecular Biology Laboratory (EMBL), and GenBank at NCBI. These three organizations exchange data on a daily basis. Geographic Coverage (i.e. geographic and spatial metadata) consists of information about where the research project took place, where the samples were collected, and any spatial or geographic reference that may provide a context for the data. Grant Application Criteria for Conservation and Sustainable Usage of Marine Biodiversity; Canadian Healthy Natural Sciences and Engineering Research Council (NSERC) Strategic Networks program, and which has been approved for funding by NSERC. (Research Agreement) 17

19 Interactive Map is a filterable map. The interactive map displays a database table using Google Fusion Tables application. Fusion Table application, is like a ACCESS, by allowing users to filter and search the dataset as a tool to explore the data. ISDM (i.e. Integrated Science Data Management) manages and archives ocean data collected by Fisheries and Oceans Canada (DFO), or acquired through national and international programmes conducted in ocean areas adjacent to Canada, and to disseminates data, data products, and services to the marine community in accordance with the policies of the DFO. KNB (i.e. Knowledge Network for Biocomplexity) is an international repository intended to facilitate ecological and environmental research. Metadata Record (i.e. the data record metadata) is detailed information about the specific data record(s). NBII (i.e. National Biological Information Infrastructure) is a broad, collaborative program to provide increased access to data and information on the nation's biological resources. Network Code Data Management Team means the team, set up by the CHONe Board of Directors to manage the Data. They are responsible for undertaking all data management and data rescue process to ensure legacy. Data Policy is outlines the overall objectives for management of CHONe data, as well as underlying principles and guidelines (i.e. data, ownership, authorship, sharing, handling practices, access and usage) to help meet the CHONe Data Repository is a secure data record storage location for the storage of data files (e.g. text, csv, spreadsheet, etc). These data files stored within the data repository are safe and secured against loss. It is recommended that raw data be uploaded immediately after collection, and then processed data and analysed data be uploaded after processing and analysis is complete, respectively CHONe Research Agreement is the Canadian Healthy Oceans Network (CHONe) Agreement entered into on January 22,

20 Research Data (or data) is data collected, observed, or derived for the purpose of analysis to produce and validate original research results. Research data refers to any and all data, in any format or medium, that relates to or support CHONe research (Research Agreement, Section 2). Theme (or theme) refers to the 3 CHONe Research Themes: Marine Biodiversity, Ecosystem Function and Population Connectivity, as set out in the grant application. Theme leaders refer to individual investigators that are responsible for the management of the 3 CHONe Research Themes: Marine Biodiversity (Kim Juniper (UVic) and Peter Lawton (DFO-SABS)), Ecosystem Function (Philip Archambault (QUAR) and Christopher McKindsey (DFO-IML) and Population Connectivity (Anna Metaxas (DAL) and Pierre Pepin (DFO-NAFC), as set out in the grant application. Project Code is the code assigned to each of the 36 projects (e.g. MB-01, MB-02, EF-01, EF-02, PC-01, PC-02, etc). Project denotes the 36 CHONe research project grants awarded to investigators (e.g. MB-01, EF-01, PC-01, etc). CHONe research project means a research project conducted by one or more of the investigators in accordance with the Grant Application and to which the CHONe Board of Directors has allocated funding (Research Agreement, Section 2) Project leads refer to the individual investigators responsible for 36 CHONe research project grants awarded to investigators, as set out in the grant application. Project Title is the title of the project. Subproject refers to individual student projects and other initiatives within those 36 CHONe research project grants. Subproject leads refer to the individual investigator, postdoc or student responsible an individual subproject (i.e. student projects and other initiatives) within the 36 CHONe research project grants. Subproject Abstract no subproject exists (e.g. thesis, thesis chapter or publication). Subproject Code is the code assigned to individual student projects (e.g. thesis) and other researcher ID. 19

21 Subproject Identifier identifies each data record (includes the data record, record metadata and documentation) associate with each subproject (e.g. a, b, c, d, e, f, g, etc.). Basically, it identifies the different data records used for each thesis data chapter or publication. The subproject identifier may not be necessary for all subprojects. Subproject Title is the title of the subproject. OBIS (i.e. Ocean Biogeographic information System) seeks to absorb, integrate, and assess isolated data records into a larger, more comprehensive pictures of life in our oceans. It provides a portal or gateway to many data records containing information on where and when marine species have been recorded. Processed data is the quality controlled, processed, analyses, descriptions, and conclusions prepared as data records, outputs, reports or papers Public Data Repository (e.g. DataONE, DRYAD, GBIF, KNB, Pangea) for long-term data preservation, accessibility, discovery and reuse, and available fully and freely to the public. Raw data is information recorded as notes, images, video footage, paper surveys, computer files, etc., pertaining to a specific research project. Raw data is collected by Research Funding is all sources of support for the work. Support includes research and educational grants, salary or other supports, contracts, gifts, and departmental, institutional and support Reused data is data created by researchers for one purpose and used by another set of researchers at a later date for a completely different research agenda Taxonomic Coverage (i.e. taxonomic metadata) consists of species information, such as taxonomic authority (e.g. World Registry of Marine Species), taxonomic class. Unique Identifier is the unique code for each subproject (or project if no subproject exists), which is assigned by the data management team. 20