ODUM INSTITUTE DATA ARCHIVE
About the Archive
The Odum Institute Data Archive is a leader in research data stewardship, with over 50 years of experience beginning with the acquisition of the Louis Harris Data Center in 1965. Our longstanding commitment to data access and research transparency has been a driving force behind ongoing efforts to enhance our infrastructure, workflows, and policies to ensure that the data assets in our care remain FAIR—findable, accessible, interoperable, and reusable–now and into the future.
We are home to one of the largest catalogs of social science research data in the U.S. which includes the Harris Polls, North Carolina Vital Statistics, and the most complete collection of 1970s U.S. Census data. In addition, we manage and provide access to the UNC Dataverse, a web-based data repository, that enables scientists, research teams, scholarly journals, and other members of the UNC research community to archive and share their own datasets.
Our mission is to provide trusted long-term preservation and stewardship of research data assets to broaden scientific inquiry, promote research reproducibility, and foster data fluency now and into the future. We recognize that scientific reproducibility is a primary concern among members of the research community and its stakeholders. Because good data management and curation is a precondition for scientific reproducibility, we offer services for data management plan development and implementation, finding & accessing data, data management training & education, and data curation for reproducibility training.
To demonstrate its commitment to achieving standards for trusted digital data repositories, the Odum Institute Data Archive has earned the 2014-2017 Data Seal of Approval (DSA) and the 2020-2022 CoreTrust Seal. The CoreTrust Seal (formerly the Data Seal of Approval) is awarded to repositories that have been recognized among the archives community as a trusted source of data based on evidence of organizational infrastructure, digital object management, and technology support.
Odum Institute Data Archive policies are informed by policies and guidelines developed collaboratively by the members of the Data Preservation Alliance for the Social Sciences (Data-PASS). Our systems and processes were further developed with industry standards and best practices for trustworthy digital data repositories in mind.
In collaboration with partner institutions and colleagues, our grant-funded research projects keep us abreast of the needs of our users, engaged with our own communities, and enhance our knowledge and skills in data management, reproducibility, and data repository development. Our projects build upon current and emerging research and give back to the users and communities we support every day.
- Journal-based Data Policy Implementation
- Confirmable Reproducible Research (CoRe2)
- Curating for Reproducibility (CURE)
- Increasing the Value of Open Access Through Open Data Publication Policies
- CRADLE Research Data Management and Sharing MOOC (Project Website)
- 10 Things for Curating Reproducible and FAIR Research (RDA CURE-FAIR Working Group)
Data Management & Sharing
Data management refers to the activities that support long-term preservation, access, and use of data. This includes, but is not limited to:
- Planning for data management
- Describing, formatting, and storing data
- Curating, archiving, and sharing data
- Using reproducible research best practices
The goal of data management is to ensure that your data are discoverable, interpretable, and re-usable by future researchers. In addition, data management and reproducible research practices help sustain the value of your data and allow others to verify and build upon published results.
|Archival Information Package (AIP)||“an information package that is used to transmit archival objects into a digital archival system, store the objects within the system, and transmit objects from the system.” (ISO 14721: The Reference Model for an Open Archival Information System)|
|Data||The National Science Foundation’s definition describes data as something “determined by the community of interest through the process of peer review and program management” (National Science Foundation).|
|Data management||As defined by NOAA's Administrative Order 212-15 "consists of two major activities conducted in coordination: data management services and data stewardship. They constitute a comprehensive end-to-end process including movement of data and information from the observing system sensors to the data user. This process includes the acquisition, quality control, metadata cataloging, validation, reprocessing, storage, retrieval, dissemination, and archival of data.”|
|Data Curation||As defined by The University of Illinois’ Graduate School of Library and Information Science “the active and ongoing management of data through its life cycle of interest and usefulness to scholarship, science, and education. Data curation activities enable data discovery and retrieval, maintain its quality, add value, and provide for reuse over time, and this new field includes authentication, archiving, management, preservation, retrieval, and representation.”|
|Designated Community||As defined by ISO 14721: The Reference Model for an Open Archival Information System (OAIS) “An identified group of potential Consumers who should be able to understand a particular set of information. The Designated Community may be composed of multiple user communities. A Designated Community is defined by the Archive, and this definition may change over time.”|
|Dissemination Information Package (DIP)||The materials delivered to the data consumer through the archive system is the dissemination information package. This package is the final product after the submission information package has been successfully transformed into an archival information package.|
|Ingest||Establishes evidence of authenticity and ensures that files within the Submission Information Package (SIP) are in proper formats and include necessary documentation. Data repositories may also perform additional tasks such as checks for confidential information and data quality reviews. (ISO 14721 Reference Model for an Open Archival Information System)|
|Metadata||Defined as structured information that describes, explains, locates, and otherwise represents something else. Metadata allows data to be found and interpreted. At a minimum, one needs to know who created the data, when the data were created or published, and a title or descriptive name used to refer to the dataset.|
|Open Access||As defined by SPARC “Open Access is the free, immediate, online availability of research articles combined with the rights to use these articles fully in the digital environment. Open Access is the needed modern update for the communication of research that fully utilizes the Internet for what it was originally built to do—accelerate research.”|
|Open Archival Information System (OAIS)||The OAIS model presents a high-level framework for understanding archival concepts, defines elements and processes within digital repositories, and establishes a set of responsibilities for the long-term preservation of digital information. (ISO 14721 Reference Model for an Open Archival Information System)|
|Open data||As defined by the Open Definition “Open data is data that can be freely used, re-used and
redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike.”
|Personally identifiable information (PII)||Data which includes variables and observations that contain
information which could potentially be used to deduce a participant or participants within a study. This
information is highly sensitive and should either be removed from or recoded within the data in such a way that deductive disclosure risk is minimal.
|Protected Health Information (PHI)||Similar to personally identifiable information, protected health
information within data could include variables or observations that contain specific health information that might lead to deductive disclosure of a participant(s).
|Reproducibility||As defined by Pröll & Rauber, “An experiment is reproducible, if and only if consistent,
scientific results can be obtained, by processing the same data with the same algorithms using the same tools. For an experiment to be reproducible, we need to have knowledge of at least the following
• Research data and metadata used
• Methods applied in the experiment
• Tools, software and execution environment used in the experiment.
|Sensitive data||Data that contain sensitive variables and observations (PII and/or PHI) that could lead to
the identification of the participant(s) of the study. Any human subjects research must undergo a review
before being approved to ensure that sensitive data is properly managed, secured, and stored with limited access and/or complete restricted access.
|Submission Information Package (SIP)||The files received directly from the data producer are called the submission information package. These files will undergo processing in order to create an Archival
Information package (AIP).
Research data management helps to ensure that others–or your future self–will be able to interpret and use your data for verification, extension, and teaching. To be effective, however, data management tasks should be performed during all stages of the research lifecycle. You can find research data management training and resources at the links below.
- DataONE Data Management Modules: The Data Observation Network for Earth (DataONE) offers a series of education modules on essential data management topics including data management planning, quality control, metadata, and data protection.
- Guide to Social Science Data Preparation and Archiving: This guide published by the Inter-university Consortium for Social and Political Research (ICPSR) provides in-depth information on data management tasks required for eventual data archiving and sharing.
- MANTRA Research Data Management and Training: A self-paced online course for students, research faculty, information professionals, and others responsible for managing research data.
- Project TIER: Project TIER (Teaching Integrity in Empirical Research) offers tools, methods, and instruction on transparent research practices, including the TIER Protocol. The TIER protocol is a framework for documenting and organizing research artifacts to support reproducibility.
- Research Data Management and Sharing: This 5-week Coursera massive open online course (MOOC) provides an introduction to research data management and sharing concepts and strategies.
Several tools are available to assist with data management. Below is a list of selected tools that support important aspects of data management at various points throughout the research lifecycle.
- Carolina Data Acquisition and Reporting Tool (CDART): Developed by the UNC Collaborative Studies Coordinating Center and NC TraCS, CDART is a clinical research data management tool for project planning and design, data capture, quality assurance, analysis, and reporting.
- Code Ocean: Code Ocean is an online tool for collaborative research that enables analysis code scripting, execution, and sharing in the cloud.
- DMPTool: The Odum Institute Data Archive sponsors the DMPTool, which is a free online “wizard” tool for creating data management plans that align with funding agency policy requirements.
- Open Science Framework (OSF): The Open Science Framework is a free online tool that supports collaborative research project management by providing a platform for sharing materials and data within a research team or among distributed teams.
- Project TIER: Project TIER (Teaching Integrity in Empirical Research) offers tools, methods, and instruction on transparent research practices, including the TIER Protocol. The TIER protocol is a framework for documenting and organizing research artifacts to support reproducibility.
- Qualitative Data Repository: UNC is an institutional member of QDR, which provides qualitative data curation and repository services along with resources on managing qualitative data. UNC affiliates who would like to submit their qualitative data to QDR for curation and publication should contact firstname.lastname@example.org.
- The UNC Information Security Office provides information on requirements for protecting sensitive and proprietary data in accordance with ITS policies.
- UNC Dataverse is an open-source web-based repository platform available to UNC faculty, students and staff for archiving, sharing, and accessing research data. See Data Repository: UNC Dataverse for more information.
- Carolina Digital Repository (CDR) is a digital archive for scholarly materials produced by members of the University of North Carolina at Chapel Hill community. The main goal of the CDR is to keep UNC digital scholarly output safe, accessible and discoverable for as long as needed.
- REDCap is a secure web platform for building and managing online databases and surveys. REDCap’s streamlined process for rapidly creating and designing projects offers a vast array of tools that can be tailored to virtually any data collection strategy.
FUNDING AGENCY DATA SHARING REQUIREMENTS
Many federal, non-profit, and private funding agencies have issued policies requiring researchers to submit a data management plan (DMP) with their proposal packages. These DMPs describe how data will be collected, used, stored, secured, and shared during and after the project ends. Each funding agency has their own requirements for constructing a DMP; however, a variety of tools and resources are available to assist in understanding and meeting those requirements.
DMPTool: The Odum Institute Data Archive sponsors the DMPTool, which is a free online “wizard” for creating data management plans that align with funding agency policy requirements. The DMPTool provides customized templates tailored to specific funding agency data sharing policies making it easy to generate a robust data management plan that meets all requirements of that particular agency. Quick Start Guide
NIH Desirable Characteristics of a Data Repository: The National Institutes of Health have created a list of desirable characteristics researchers should look for when selecting a data repository as part of their data management plan. These characteristics ensure the data deposited into a repository are preserved, accessible, and reusable even after the end of the project’s active phase.
Unless specified in the data sharing policy requirements, UNC researchers may deposit appropriate data using UNC-based repositories. The table below describes each repository and its alignment with the NIH-stated desired characteristics.
|Characteristics||UNC Dataverse||Carolina Digital Repository|
|Unique Persistent Identifier||Yes||UNC Dataverse mints a DOI (digital object identifier) for all published datasets. The DOI is a unique persistent identifier provided through DataCite.||Yes||The CDR creates DOIs automatically for all public deposits. This process runs overnight and the DOI will be available on your article record the morning after deposit. Please note that DOIs will not be added to works which are embargoed, restricted to UNC-only access, or private.|
|Long-Term Sustainability||Yes||See the Odum Institute Data Archive’s Digital Preservation Policy: Financial Sustainability section for information on the Odum Institute Data Archive’s commitment to a long-term sustainable and accessible data repository.||Yes||See the Carolina Digital Repository’s Preservation Policy for more information.|
|Metadata||Yes||Offers citation, domain-specific, and file-level metadata which provide robust records for increased discoverability. Metadata can be exported in the following formats: Dublin Core, DDI (Data Documentation Initiative Codebook 2.5), DDI HTML Codebook (A more human-readable, HTML version of the DDI Codebook 2.5 metadata export), DataCite 4, JSON (native Dataverse format), OAI_ORE, OpenAIRE, Schema.org JSON-LD.||Yes||Provides limited citation and descriptive metadata at the record-level only.|
|Curation and Quality Assurance||Yes||The Odum Institute Data Archive provides high-quality curation and data management services for a fee that can be included in grant proposals and data sharing budgets. Contact the Odum Institute Data Archive for a quote.||No||The Carolina Digital Repository does not offer curation or quality assurance services.|
|Free and Easy Access||Yes||All data producers are encouraged to share their data as openly as possible. UNC Dataverse makes data publicly available upon publishing by default; however, data producers may also customize access to their data using the access restrictions feature. |
UNC Dataverse is currently unable to handle sensitive data containing PII, PHI or other human subjects protected data. Please contact the Odum Institute Data Archive for alternative options with regards to data that cannot be publicly shared.
|Yes||The Carolina Digital Repository encourages public sharing of research and its outputs; however, access restrictions are offered as a feature and include: UNC-Chapel Hill Only access, Embargo, and Private.
The CDR is unable to handle sensitive data that falls under the ‘Sensitive Information’ categories as designated by UNC.
|Broad and Measured Reuse||Yes||UNC Dataverse does not require fees to access any of its holdings. All datasets are publicly available, unless the original data producer has placed access request restrictions upon the data. In those instances, users may request access to the data and undergo an approval process with the data producer. |
Dataset downloads, as well as a guestbook tracking feature, permit data owners to review the number of downloads by users and even track usage by collecting information on who, when, and why a dataset was downloaded/accessed.
|Yes||All data, unless designated by the depositor, are deemed publicly available.
CDR does not make available download statistics on dataset records; however, they do track page views for each record.
|Yes||All datasets deposited to CDR start with a default CC0 license. Depositors may select CC-BY or No License when depositing their materials.
|Security and Integrity||Yes||See the Odum Institute Data Archive Data Security Guidelines for more information on measures in place to ensure the security and integrity of data holdings within UNC Dataverse.||No||Unknown.|
|Confidentiality||No||At this time, UNC Dataverse cannot handle sensitive data containing PII, PHI or other human subjects protected data. Please contact the Odum Institute Data Archive for alternative options with regards to data that cannot be publicly shared.||No||Data submitted to the Carolina Digital Repository must not include any personally identifiable, encrypted, or sensitive information as defined by UNC. More information about personally identifiable and sensitive information at UNC.|
|Common Format||Yes||File formats such as Stata, SPSS, R, Excel (xlsx), CSV and TSV are ingested in UNC Dataverse as tabular data files, which generates the following: a tab-delimited data file (with the variable names in the first row), the original file uploaded by the user, an R data version of the file (if the original file was not in R format), variable metadata (as a DDI Codebook XML file), and data file citation (currently in either RIS, EndNote XML, or BibTeX format). All other data formats are preserved at the bit-level only. |
It is recommended that data producers share data files in the most software agnostic or open source data format possible, or the most commonly used format within your community.
|Yes||All data, regardless of format, are preserved at the bit-level only. The CDR recommends depositors share data in open source, non-proprietary data formats.|
|Provenance||Yes||Data provenance can be included at the individual data file-level using the UNC Dataverse Provenance option in the data file edit drop-down menu. Data producers have the option of sharing a provenance file or including the text in the provenance text field. |
The provenance should describe where the data originated from, any transformative actions taken on the data, and any and all persons or organizations associated with that file.
|No||The Carolina Digital Repository does not have mechanisms in place for capturing provenance information.|
|Retention Policy||Yes||It is the Odum Institute Data Archive’s mission to provide trusted long-term preservation and stewardship of research data assets to broaden scientific inquiry, promote research reproducibility, and foster data fluency now and into the future. As such, the Odum Institute is committed to ensuring access to and preservation of research data in perpetuity. The Odum Institute Data Archive Digital Preservation Policy outlines this effort in greater detail.||Yes||All datasets are retained for a minimum of 10 years and will then be reviewed by the CDR staff. The CDR retains the right to refuse data submissions if circumstances warrant. See the Carolina Digital Repository Data Deposit Policy for more information.|
Most projects at UNC are funded via one of the following agencies. Each agency has their own data sharing policy and requirements:
|National Institutes of Health||Scientific Data Sharing Policy|
|National Science Foundation||Data Management Plan Requirements|
|Department of Defense||Plan to Establish Public Access to the Results of Federally Funded Research|
|National Institute of Environmental Health Sciences||Data Management and Sharing Policies|
|National Cancer Institute||Data Sharing and Public Access Policies|
|Department of Homeland Security||Plan to Support Increased Public Access to the Results of Research Funded by the Federal Government|
Data Repository: UNC Dataverse
The Odum Institute hosts and manages UNC Dataverse, a trusted data repository available to UNC faculty, students, and staff for long-term data archiving and data sharing. Along with preserving data, researchers can also find valuable datasets that others have made publicly available, including those donated to the Odum Institute Archive Dataverse.
WHY UNC DATAVERSE?
Dataverse is an open-source repository software application for archiving, sharing, and accessing research data. It was developed by the Institute of Quantitative Social Science (IQSS) at Harvard University and supports the FAIR Principles for scientific data management and stewardship by ensuring data are findable, accessible, interoperable, and reusable.
UNC Dataverse is a viable option for many UNC researchers needing to deposit their research data in response to the increasing requirements of funding agency data sharing mandates. It offers several value-added features to enhance data discovery, access, and use:
- Automatic generation of data citation with DOI
- Standardized descriptive metadata
- Support for restricted file access
- User activity tracking and download metrics
- Faceted browse and advanced search
- Dataset version tracking
- Data exploration tools
- Rich data support for tabular data
- File format normalization for preservation
- APIs for tool interoperability and integration
UNC DATAVERSE SELF-DEPOSIT
We encourage UNC researchers to deposit their research data in a professional data repository. There is no cost to self-deposit your data in UNC Dataverse, which has no filetype or disciplinary domain restrictions. If you would prefer that the Odum Institute handle data file preparation and deposit, please see our Consultations & Services.
Please review the information below and Archive Policies as you prepare data files for archiving and sharing to help ensure your data meet standards for long-term data preservation, access, and reuse.
Contextual information is essential for appropriate interpretation and use of data. Documentation such as README files, methodology reports, codebooks/data dictionaries, and instruments should always be deposited alongside dataset files. Researchers should consider what types of information are necessary for others to understand the creation, manipulation, content, and structure of their data files.
In addition to documentation, it is important that datasets be described using machine-readable standardized metadata in order to enable and enhance findability and interoperability. UNC Dataverse provides a minimum, required set of descriptive metadata which facilitates accurate identification of the data for discovery and citation purposes. Domain-specific metadata blocks are also available and allow for rich descriptions that enhance independent and informed use of the data.
We strongly encourage researchers to provide as much metadata as possible when depositing datasets to UNC Dataverse.
The file formats used by researchers are often informed by individual research practices and domain-specific standards. However, to avoid risks to long-term data preservation, access, and use that can arise from software obsolescence, the Odum Institute Data Archive recommends that data files be submitted in formats that are widely adopted, non-proprietary, free of external software dependencies, and well-documented.
UNC Dataverse automatically generates tab-delimited preservation copies of data files for specified file formats. This optimizes preservation capabilities and allows users to both explore tabular data using the UNC Dataverse interface and download data in multiple file formats.
The following file formats are supported with optimized preservation:
|IBM SPSS||.por OR .sav||Versions 7 to 22|
|Stata||.dta||Versions 4 to 15|
|R||.RData||Versions 1 to 3|
|Microsoft Excel||.xlsx||.xls is not supported|
|Comma-separated values||.csv||Limited support|
To ensure that supporting documentation are rendered properly, we prefer the following file formats for document files such as README files, codebooks/data dictionaries, instruments, and methodology reports.
|Adobe Portable Document Format||.pdf/ua OR .pdf/a OR .pdf|
Other File Types
While UNC Dataverse accepts all file formats and preserves them at the bit level, data depositors should still consider the long-term sustainability of every file format. Software dependencies, proprietary status, limited adoption, lack of public documentation, and other factors can negatively impact the ability to render files in the future. Refer to the Library of Congress Recommended Formats Statement when selecting file formats not listed above for UNC Dataverse deposit, or contact us for guidance on identifying a suitable file format or converting files to a preferred format for long-term preservation.
Odum Institute Data Archive systems and workflows are designed to uphold all applicable laws and regulations governing the protection of human subjects. Standards and procedures for handling and storage of sensitive and confidential data are outlined in our Archive Policies.
For information on available resources for archiving confidential data, please contact email@example.com.
UNC DATAVERSE MEDIATED & FULL SERVICES
The Odum Institute Data Archive offers a wide variety of services to assist UNC researchers, research teams, institutions, centers, and university departments with curating, depositing, and using UNC Dataverse. Please see our Consultations & Services section for more information on our free and for-fee service options.
ODUM INSTITUTE ARCHIVE DATAVERSE
The Odum Institute Archive Dataverse is home to one of the largest catalogs of social science research data in the U.S. Our collections include:
We actively seek donations of data that complement the scope of our collections, in particular those datasets that focus on topics related to the Southern region of the United States and state-level public opinion polls. The Data Archive also prioritizes data considered to be at risk of being lost.
If you would like to donate your data to the Odum Institute Archive, please contact us at firstname.lastname@example.org.
Consultations & Services
The Odum Institute Data Archive provides free consultations to all UNC students, faculty and staff. We are available to answer questions and offer guidance on any of the topics listed below:
For researchers submitting a proposal to a funding agency with data sharing requirements, you may want to have your data management plan reviewed before submission. Odum Archive staff will review your DMP for both completeness and appropriateness. If necessary, we will offer recommendations for improving your data management plan, or assist in identifying the most appropriate repository for your research data.
Initial data management plan review consultations are free of charge. Odum Archive requires that you put your plan into the DMPTool so that we may make comments and edit suggestions directly. Please submit a request for review using the form linked below:
Searching for publicly available research data for secondary reuse can be overwhelming. Students, faculty, and staff are encouraged to reach out to Odum Archive staff for assistance in locating data that may supplement their research or coursework. Please contact email@example.com with questions pertaining to identifying public-use data.
We have also provided a variety of resources below to get you started in your search.
|AddHealth||https://www.cpc.unc.edu/projects/addhealth||AddHealth is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States starting in 1994-95 and following their lives through adulthood. Follow-up interviews were also conducted from 2016-2018 to collect data as the cohort enters their fourth decade of life.|
|American Community Survey (ACS)||https://www.census.gov/programs-surveys/acs/||The ACS is an annual survey that collects individual-level demographic, housing, social, and economic data.|
|American Housing Survey (AHS)||https://www.census.gov/programs-surveys/ahs/data.html||The AHS is a biennial survey that collects housing unit data that includes information on size and composition of housing, vacancies, characteristics of occupants, housing costs, etc.|
|American National Election Studies (ANES)||https://electionstudies.org/data-center/||The ANES has collected individual-level data on voting, public opinion, and political participation for most general and midterm election years.|
|Association of Religion Data Archives (ARDA)||http://www.thearda.com/Archive/browse.asp||ARDA provides access to religion-related data that include both U.S. and international-based datasets.|
|Behavioral Risk Factor Surveillance System (BRFSS)||https://www.cdc.gov/brfss/annual_data/annual_data.htm||The BRFSS collects annual individual-level survey data related to health-related risk behaviors, chronic health conditions, and use of preventive services.|
|Bureau of Economic Analysis (BEA)||https://www.bea.gov/itable/||The BEA maintains national, industry, international, regional economic data that includes GDP, personal income, industry input-output, and international transactions and direct investments.|
|Bureau of Labor Statistics||https://www.bls.gov/data||The Bureau of Labor Statistics provides access to data on inflation and prices, employment, pay and benefits, spending, occupations, and other economics-related topics.|
|Data.gov||http://Data.gov||Data.gov is a database portal with links to access datasets produced by federal, state, and city governments, as well as other institutions in the United States.|
|Data.gov.uk||http://Data.gov.uk||Data.gov.uk is a database portal with links to access data produced by government agencies, public bodies, and local authorities in the U.K.|
|Demographic & Health Surveys (DHS) Program||http://dhsprogram.com/data/||The DHS program has collected nationally representative survey data related to population, health, HIV, and nutrition from over 90 countries.|
|Eurostat||http://ec.europa.eu/eurostat/data/database||Eurostat provides access to economic, demographic, and environmental data about European countries and regions.|
|FRED Economic Data||https://fred.stlouisfed.org/||FRED provides access to a wide variety of economic data including banking, labor markets, national accounts, and prices data, both U.S.- and international-based.|
|General Social Survey (GSS)||http://gss.norc.org/Get-The-Data||The GSS collects individual-level survey data from Americans to study trends in attitudes and behaviors towards a variety of topics including crime, civil liberties, morality, and well-being.|
|Global Health Observatory (GHO) Data||http://apps.who.int/gho/data/node.home||The GHO provides access to World Health Organization data for its 194 member states. Data include over 1,000 health-related indicators.|
|HealthData.gov||https://www.healthdata.gov/||HealthData.gov is an access portal to health-related data produced by government agencies, public bodies, and local authorities in the U.S.|
|Inter-university Consortium for Political and Social Research (ICPSR)||https://www.icpsr.umich.edu/icpsrweb/||ICPSR maintains a data archive of social and behavioral sciences datasets. It also hosts several thematic collections of data related to education, criminal justice, arts and culture, and aging.|
|Latin American Public Opinion Project (LAPOP)||http://www.vanderbilt.edu/lapop/about.php||LAPOP has collected public opinion surveys in the 28 countries of North, Central, and South America, as well as countries in the Caribbean. IRB approval is required for access.|
|National Center for Education Statistics (NCES)||https://nces.ed.gov/datatools/||NCES collects data on the condition of education in the U.S. Data topics include literacy, early childhood, elementary and secondary education, and postsecondary education. Collections include international data.|
|National Centers for Environmental Information (NCEI)||https://www.ncei.noaa.gov/||NCEI provides access to environmental data including weather and climate, coastal, oceanic, and geophysics data.|
|Pew Research Center||http://www.pewresearch.org/||Pew Research Center provides access to data produced from Pew Research public opinion polling, and other empirical research studies. Data topics include politics, media, religion, Hispanic trends, and other contemporary issues.|
|ProQuest Statistical Abstract of the U.S.||http://statabs.proquest.com/sa/index.html||The ProQuest Statistical Abstract of the U.S. provides summary statistics on social, political, and economic conditions of the U.S.|
|Roper Center||https://ropercenter.cornell.edu/||The Odum Institute sponsors UNC-affiliate access to Roper Center resources. The Roper Center offers both U.S. and international public opinion polling data dating back to the 1930s.|
|Sheps Center||https://www.shepscenter.unc.edu/data/||The Cecil G. Sheps Center for Health Services Research seeks to improve the health of individuals, families, and populations by understanding the problems, issues and alternatives in the design and delivery of health care services.|
|Survey of Consumer Finances (SCF)||https://www.federalreserve.gov/econres/scfindex.htm||Every three years, the Federal Reserve Board conducts a cross-sectional survey of U.S. families to collect data on income, demographics, pensions, and balance sheets.|
|UCI Machine Learning Repository||https://archive.ics.uci.edu/ml/index.php||The UCI Machine Learning Repository offers a collection of data from various disciplines used for empirical analysis of machine learning algorithms.|
|UK Data Archive||http://www.data-archive.ac.uk/||The UK Data Archive hosts the UK’s largest collection of social and economic data. Collections include UK surveys, international macrodata, and census data.|
|UNC Dataverse||https://dataverse.unc.edu/||UNC Dataverse provides access to almost 25,000 research datasets including the Louis Harris polls, North Carolina Vital Statistics, and the most complete collection of the 1970 United States Census.|
|UNICEF Data||https://data.unicef.org/||UNICEF data hosts data related to children and women collected from more than 100 countries worldwide through the Multiple Indicator Cluster Surveys (MICS) household survey program.|
|Uniform Crime Reporting (UCR) Statistics||https://www.ucrdatatool.gov/||The FBI’s UCR Program collects crime data on the national, state, city, and county levels.|
|U.S. Census||https://data.census.gov/cedsci/||The Census Bureau is the leading source of quality data about the nation's people and economy.|
|Voting and Elections Collection||http://library.cqpress.com/elections/download-data.php||Downloadable national- or county-level data for current or historical elections for the offices of president, house, senate, and governor.|
|World Bank||https://www.worldbank.org/||The World Bank Group is one of the world’s largest sources of funding and knowledge for developing countries|
For researchers collecting qualitative data, we provide qualitative data management support, training, and institutional access to the Qualitative Data Repository. As institutional members, UNC faculty and staff may be able to deposit their materials to the Qualitative Data Repository free-of-charge.
Our qualitative data expertise ensures your data are managed, curated, shared, and preserved for the long-term to increase access and re-use of your research. If you would like to learn more about how to manage and preserve your qualitative data, please contact firstname.lastname@example.org.
Interested in learning more about Dataverse and if it is appropriate for your research project? Odum Archive staff offer free UNC Dataverse consultations with a brief walkthrough of the platform and its features. In this consultation, we will learn about your project needs and let you know the available options to support sharing and preservation of your research data. If Dataverse is not an appropriate repository, we will help you identify the best option,
Most consultations take under an hour and will be scheduled virtually unless in-person is required. To schedule a consultation, please email email@example.com with the following information:
- Description of your project & project team members
- The type(s) of data being collected and their format(s) and file sizes
- (If available) The funding agency data sharing mandate
- Your deadline for completion
Odum Archive staff provide free lectures and presentations for graduate students, university departments, and research project teams on data management best practices, standards and tools. We also offer sessions on reproducible research practices to support open and transparent science.
If you would like to invite us to speak to your group, please contact us at firstname.lastname@example.org. Lectures are offered both in-person and virtually.
The Odum Institute Data archive offers support services across the research lifecycle ranging from data management planning to data curation and archiving. Learn more about our services below and contact us to request a quote.
Researchers and project teams wanting to partner with the Odum Institute Data Archive to support their data management workflow and plan implementation, should contact email@example.com early in their proposal writing process. We are available to assist in developing a plan and workflow appropriate to your project’s needs that will meet funding agency data sharing requirements.
We recommend providing the following information when contacting us to schedule a consultation for collaboration:
- Description of project
- Funding agency and data sharing mandate
- Types of data anticipated
- Will any of these data be sensitive or contain personally identifiable information or protected health information?
- List of project team members
During the initial consultation we will discuss options for the types of service we provide ranging from data management workflow development to data curation and archiving. If our collaboration is appropriate, we will provide a quote for services agreed upon, a letter of support (as needed), as well as assist in writing and reviewing the data management plan before proposal submission (if appropriate).
The Odum Institute Data Archive offers customized training for project teams that include workflow development and implementation, UNC Dataverse workshop, as well as tailored guidance documentation for every step of your project workflow. Training sessions can be done virtually, in-person, or, for an additional fee, we will create a video tutorial that can be shared with your entire team.
This level of support is best for teams who want to handle the data management and sharing components of their project, but may need assistance determining the most suitable workflow and getting started.
If you would prefer the guidance of Odum Institute Data Archive staff to help ensure compliance with archival standards and best practices, we offer researchers the option of selecting appropriate services to meet their research project needs. These services are available to address specific areas of a data management workflow pertaining to the curation and archiving of your data. Services include:
Odum Archive staff will review all available documentation for completeness and understandability. We will offer recommendations for improvement as needed. Once the documentation is complete, we will create a preservation version of the documentation to be included in the final dataset record in UNC Dataverse (or your repository of choice).
Our staff will review the data file(s) for any sensitive information such as protected health information or personally identifiable information. All data being shared in the UNC Dataverse must be free from any sensitive or potentially identifying information. We will make recommendations for cleaning your data before submitting it to a repository for public sharing.
UNC Dataverse Branding & Metadata Template Creation
We are available to customize your UNC Dataverse to include logos, website links, descriptions, permissions, and group access. In addition, we will develop custom metadata templates to make dataset creation easier on your project team.
Custom Upload, Review, and Publishing Guidance
For larger teams, we can create custom guidance documents that will walk team members through the entire upload and publish workflow for your dataverse. Custom documentation includes step-by-step visuals, definitions and explanations of processes, as well as contact information for relevant project managers and dataverse administrators.
Full UNC Dataverse Support
For those researchers who would prefer the Odum Institute Data Archive manage all aspects of their data management and sharing workflows, including data and documentation review, dataverse and dataset creation, file normalization, ingest, and permissions, please provide the following information:
- Description of project
- Funding agency and (if available) data sharing mandate
- Types and file sizes of data
- Are any of these data sensitive or do they contain personally identifiable information or protected health information?
- List of project team members
- Timeline for completion
In order to schedule a consultation and receive a quote, please contact firstname.lastname@example.org with a description of which service(s) you are interested in.
We offer data verification implementation services for journals with data verification policies, or those journals who may be interested in increasing the requirements of their current data policies by requiring verification of manuscript results before manuscript publication. Data verification services include data curation, data archiving, and data verification workflows. Quotes are available by request. Please contact email@example.com for more information.