Collaborative Markup of Library and Research Data: Examples from OCUL

Presentation at the North American Data Documentation Conference (NADDI) 2013This presentation will focus on collaborative efforts to capture, store, and disseminate social science survey data & researcher data across all of Ontario's University Libraries. Together through shared platforms and practices, collaborative markup of data using the Data Documentation Initiative (DDI) standard is possible in order to effectively deliver rich discovery services to users of library and researcher data. An overview of Scholars Portal's data services including the Ontario Data Documentation, Extraction Service and Infrastructure (ODESI), and Dataverse will highlight effective collaborative markup strategies for data.Institute for Policy & Social Research, University of Kansas; University of Kansas Libraries; Alfred P. Sloan Foundation; Data Documentation Initiative Allianc

Using RDF to Describe and Link Social Science Data to Related Resources on the Web

Kramer S, Leahey A, Southall H, Vompras J, Wackerow J. Using RDF to Describe and Link Social Science Data to Related Resources on the Web. DDI Working Paper Series. Dagstuhl, Germany: DDI Alliance; 2012.This document focuses on how best to relate Resource Description Framework (RDF)-described datasets to other related resources and objects (publications, geographies, organizations, people, etc.) in the Semantic Web. This includes a description of what would be needed to make these types of relationships most useful, including which RDF vocabularies should be used, potential link predicates, and possible data sources. RDF provides a good model for describing social science data because it supports formal semantics that provide a dependable basis for reasoning about the meaning of an RDF expression. In particular, it supports defined notions of entailment which provide a basis for defining reliable rules of inference in RDF data. Our findings are discussed in the context of social science data and more specifically, how to leverage existing metadata models to use alongside linked data. We provide a case for leveraging the Data Documentation Initiative (DDI) to enable semantic linking of social science data to other data and related resources on the Web. This document is organized into five use cases, which we consider in turn. Use cases include: linking related publications to data, linking data about people and organizations to research data, linking geography, linking to related studies, and linking data to licenses. We briefly discuss emerging or known issues surrounding the potential use of linked data within each of the defined use cases. Following these, we list more topics that could develop into additional use cases. Appendix A lists elements from the DDI-Codebook and DDI-Lifecycle specifications that are relevant to each use case

Historical map digitization in libraries: Collaborative approaches for large map series

Academic libraries are playing a role in the digitization of Canadian government documents, but maps tend to be excluded from these activities due to their unique dimensions and display requirements. Using a topographic map digitization project as a case study, this paper presents a collaborative approach to map scanning, georeferencing, and metadata creation across several Ontario universities. Collectively, the 21 institutions making up the Ontario Council of University Libraries (OCUL) possess and maintain large volumes of Canadian topographic maps. However, few OCUL universities hold complete sets of these map series. While the Canadian government’s most recent topographic maps are now available online, older editions of these maps have not been digitized. This project, currently underway at several participating universities, will enable us to share digital versions of some of our most-requested historical map series with the public at large

Navigating the Scholars GeoPortal , Demonstration (20 min)

Scholars GeoPortal provides researchers across Ontario with access to a variety of local, provincial, and national geospatial datasets. The interactive map display allows users to search for data, preview data, and download data directly. In this presentation, I will highlight some of the ways you can navigate in the portal to find and use data for research and teaching. Scholars GeoPortal is open and accessible to anyone, affiliated Ontario researchers can login to access the full collection (http://geo.scholarsportal.info/)

Building a Web Based Health Data Search Tool Using DDI

The Ontario Population Health Index of Databases (OPHID) is an index of a wide variety of quantitative information sources for and about Ontario (Canada) that reflect both the state of the health of its populations and possible explanatory variables. OPHID is a rich information resource for health researchers. The collection represents a vast improvement for the availability of metadata for health data in Ontario (and Canada as whole), where health data are often disparately collected, poorly documented, and not available or known to the public. Researchers in population health and the health sciences increasingly require high-quality health data, especially as health research becomes more evidence-based and measure-driven. This comprehensive index of health data utilizes the Data Documentation Initiative (DDI-Codebook) standard to document and describe data of varying kinds. Data sources that are of a survey, clinical, and administrative nature are described using a core set of DDI fields, with some degree of difficulty arising around consistency across the kinds of data. This presentation will provide an overview of the OPHID project goals and objectives, while focusing on the technical implementation and process by which datasets are described and marked up using the DDI standard. OPHID is a joint collaboration among the Ontario Council of University Libraries, Scholars Portal, and the Population Health Improvement Research Network (PHIRN)

Finding Historical Topographic Maps in the Scholars GeoPortal, Demonstration (20 min)

There are thousands of historical scanned maps in the Scholars GeoPortal available for open reuse. The 1:63,360 and 1:25,000 scale topographic maps were the first historical series to be inventoried and georeferenced by the Ontario academic library community for open access in 2017. Now we\u27ve added maps covering all of Ontario at the 1:50,000 scale, representing a rich set of historical topographic data to be used for all sorts of historical and longitudinal research. Join me for a demonstration of how to find, access, preview, and reuse these amazing historical maps in the GeoPortal

Research Data Discovery and the Scholarly Ecosystem in Canada : A White Paper

Research data must be discoverable to be re-used. Data discovery represents the descriptive and technical processing of data and metadata, as well as the tools and infrastructure aimed at improving access and reuse of research data on the web. A Canadian data discovery service would make it easier to find and reuse research data held in institutional and disciplinary repositories. We would like to see a service that provides a coherent, single point of access to authoritative, searchable, browsable, and machine actionable descriptions (metadata) for datasets and implements clear means for accessing them, thus increasing the likelihood of discovery and reuse of research data in Canada. In this paper, we highlight current opportunities and issues related to developing such a service in Canada. Based on a review of international and national research data repositories and data discovery services, we offer a set of guiding principles, best practices, and recommendations for data discovery: Common metadata: the descriptive information that accompanies research data should meet minimum standards to enable discovery and support data reuse. This requires a commitment to a core set of metadata components across domains. Metadata tools should accommodate multiple, overlapping metadata namespaces, i.e., descriptive terms assigned, managed, and grouped into collections of classes and attributes. We also recommend building separate, flexible metadata harvesters for indexing specialized repositories, so that domain-specific metadata and granularity can be retained in its original format. Persistent Identification: the use of global identifiers for researchers and research data. We recommend exploring a national ORCID agreement so that universities and government agencies in Canada can integrate researcher identifiers into institutional and other research management and publishing software. We also recommend registering DOIs corresponding to datasets in participating repositories with DataCite Canada. These DOIs will greatly enhance dataset discoverability via DataCite’s metadata partners (e.g. ORCID, VIVO, etc). Open Access and Programmatic Interfaces: the use of an application program interface (API) allowing one piece of software to make use of the functionality or data available to another through a set of routines, protocols, and tools. Metadata and data should be programmatically accessible for reuse and development purposes through the provision of APIs among participating repositories and data discovery platforms. Common licensing: policies and licenses should govern access to data and metadata and, whenever possible, should be minimally restrictive. We recommend the use of Creative Commons licenses for research data as they effectively communicate information about the copyright holders’ intentions and clarify usage permissions. Licensing can apply to data and metadata, although we strongly recommend that metadata be provided as openly as possible, with minimal to no restrictions on reuse in order to facilitate discovery. Collaboration: a joint commitment to shared recognition and cooperation among actors, organizations, data producers, and researchers, sometimes described as “coexistence in the scholarly ecosystem.” We emphasize that collaboration will drive improvements for data discovery in Canada. A well coordinated national project will ensure that all attempts to improve discovery and access to data will be informed and facilitated by stakeholder expectations, participation, and collaboration. Keeping stakeholders engaged and providing clear communication channels are key for the success of a national data discovery service. This paper is presented with a common goal to make research data as widely discoverable and accessible as possible, thus enhancing opportunities for data reproducibility and reuse. Enhancing data discovery is one approach to facilitating greater interoperability and discovery of scholarly outputs. Building national infrastructure to support research data discovery will greatly enhance opportunities for further integration across the scholarly ecosystem, including support for metadata, global identifiers, and open APIs.Library, UBCNon UBCUnreviewedFacultyResearche

Portage Dataverse North [Dataverse Community Meeting 2018]

Presentation at the Dataverse Community Meeting, June 14, 2018, Harvard, MA, USA.The Canadian Association of Research Libraries (CARL) Portage Network is committed to developing a community of practice devoted to strengthening the capacity of university libraries to provide expertise, services, and infrastructure for research data management in Canada. As a part of its mandate, Portage has established the Dataverse North Working Group. In Canada, some universities and regional library consortia have been providing Dataverse as a service for many years (e.g. UBC Abacus Dataverse; Scholars Portal Dataverse; and University of Alberta Dataverse). Working as a collaborative community and centered around the use of Dataverse across Canada, we surveyed users and institutional providers about their repository use, setup and configurations, and training needs. This work resulted in a proposal to create a national Dataverse North service, that would include data hosting, infrastructure development (including a bilingual interface), data preservation, training, and coordinated user support. This presentation provides an update from the Introduction to Dataverse North presented at the 2017 Dataverse Community Meeting, to our current progress in 2018 as we begin efforts to implement a national Dataverse North service.Library, UBCNon UBCUnreviewedFacult

Découverte des données de recherche et écosystème du savoir au Canada : Livre blanc

Il faut que les données de recherche soient explorables pour être réutilisées. L’exploration des données correspond au traitement descriptif et technique des données et des métadonnées ainsi qu’aux outils et à l’infrastructure visant à améliorer l’accès aux données de recherche sur Internet et leur réutilisation. Un service canadien d'exploration des données faciliterait la découverte et la réutilisation des données de recherche conservées dans des dépôts institutionnels et disciplinaires. Nous aimerions voir un service qui offrirait un point d’accès cohérent aux descriptions (métadonnées) fiables, consultables, explorables et susceptibles d’action par les machines pour les ensembles de données, et qui offrirait des moyens clairs pour y accéder, ce qui accroîtrait les chances d'exploration et de réutilisation des données de recherche au Canada. Dans le document qui suit, nous faisons ressortir les possibilités et problématiques actuelles concernant l’élaboration d’un tel service au Canada. À l’aide d’une enquête concernant les dépôts de données de recherche et les services d’exploration des données nationaux et internationaux, nous proposons un ensemble de principes directeurs, de pratiques exemplaires et de recommandations pour l’exploration des données: Métadonnées communes : Les renseignements descriptifs qui accompagnent les données de recherche doivent respecter des normes minimales pour favoriser l’exploration et soutenir la réutilisation des données. Cette exigence requiert un engagement pour un ensemble fondamental de composants de métadonnées dans tous les domaines. Les outils de métadonnées devraient permettre de multiples espaces de nommage de métadonnées – termes descriptifs assignés, gérés et regroupés en collections de catégories et attributs. Nous recommandons également de créer multiples outils de prospection de données souples pour l’indexation des dépôts spécialisés afin que l’on puisse conserver la granularité et les métadonnées propres à un domaine dans leur format original. Identification permanente : L’utilisation d’identifiants universels pour les chercheurs et les données de recherche. Nous recommandons d’envisager une entente nationale d’ORCID afin que les universités et les organismes gouvernementaux du Canada puissent intégrer des identifiants de chercheur dans des logiciels de gestion et de publication de recherche institutionnels ou d’autre nature. Nous recommandons également d’enregistrer des identifiants numériques d’objet (DOI) se rattachant aux ensembles de données dans les dépôts participants auprès de DataCite Canada. Ces DOI amélioreront grandement l’exploration des ensembles de données par l’entremise des partenaires de métadonnées de DataCite (p. ex., ORCID, VIVO, etc.). Interfaces programmatiques et à libre accès : Une interface de programmation qui permet à un composant logiciel d’utiliser la fonctionnalité ou les données mises à la disposition d’un autre par l’entremise d’un ensemble de routines, de protocoles et d’outils. Les dépôts et les services d’exploration des données participants devraient offrir une interface de programmation permettant à des programmes d’accéder aux données et aux métadonnées à des fins de réutilisation et de développement. Licences communes : Il faudrait établir des politiques d’octroi de licences pour les données et les métadonnées et, dans la mesure du possible, celles-ci devraient être le moins restrictives possible. Nous recommandons d’utiliser des licences Creative Commons pour les données de recherche puisqu’elles transmettent efficacement des renseignements sur les intentions des titulaires du droit d’auteur et qu’elles clarifient les usages autorisés. Les licences peuvent s’appliquer aux données et aux métadonnées, même si nous recommandons fortement d’offrir les métadonnées le plus librement possible, avec des restrictions minimales ou nulles sur leur réutilisation pour en faciliter l'exploration. Collaboration : Un engagement pour la reconnaissance et la collaboration partagées entre les acteurs, les organisations, les producteurs de données et les chercheurs, que l’on peut aussi qualifier de « coexistence dans l’écosystème du savoir ». Nous insistons sur le fait que la collaboration constituera le grand facteur déterminant de l’amélioration de l'exploration des données au Canada. Un projet national bien coordonné permettra de s'assurer que toutes les tentatives d’amélioration de l'exploration et de la consultation des données seront éclairées et facilitées par les attentes, la participation et la collaboration des intervenants. La mobilisation des intervenants et l’établissement de canaux de communication clairs sont essentiels à la réussite d’un service national d’exploration des données. Le document qui suit est présenté avec un objectif commun, soit celui de favoriser le plus possible l’exploration et la consultation des données de recherche, et d’améliorer conséquemment les possibilités de reproductibilité et de réutilisation des données. L’amélioration de l'exploration des données constitue une manière de faciliter l’interopérabilité et l’exploration accrues des résultats savants. L’élaboration d’une infrastructure nationale qui rehausse l’exploration des données de recherche améliorera les possibilités d’intégration additionnelle au cœur de l’écosystème du savoir, ce qui comprend le soutien pour les métadonnées, les identifiants universels, et les interfaces programmatiques à libre accès.Library, UBCNon UBCUnreviewedFacultyResearche

Dataverse for the Canadian Research Community: Developing reusable and scalable tools for data deposit, curation, and sharing

Presentation on Dataverse. For the National Data Services Framework Summit 2019