WP8 Tasks

Task 8.1: OpenAIRE data model maintenance

The OpenAIRE information space data model will be adapted to support the new back-end, front-end and knowledge extraction services. The changes will be collected and applied overtime as a consequence of the design and development of the services, and will be tracked on an ongoing deliverable, open to the public. Envisaged changes will regard: (a) the integration of publication licenses (ROMEO services), (b) description and interlinking with software entities, (c) modeling of annotations (Open Annotation Model), (d) features of data pilot plans associated to projects, (e) alignment of multiple author identifier schemes (e.g. ORCID, GoogleScholarID), (f) alignment with updates in new releases of the CERIF data model,and many more. CNR will be responsible for the collection of data model update requests, check for their applicability, and, when accepted, communicate the impact of such changes to other services.

LEADER: CNR
PARTICIPANTS: ARC, ICM, UNIBI, CERN, EKT

Task 8.2: LOD SERVICES

As a result of this task OpenAIRE will increase its technical interoperability, engage with additional user communities and explore synergies with and added value to related open content initiatives (e.g. in the Open Educational Resources). The Services will be deployed by UBONN/ARC in order to map all metadata objects in the OpenAIRE Information Space onto suitable standard vocabularies (e.g. Dublin Core, SIOC, EDM, CERIF LD) and made available as Linked Open Data as data dumps being published in regular intervals with more frequently published incremental updates. UBONN with ARC will (a) operate the interlinking between OpenAIRE LOD objects with other Linked Data resources such as DBLP, ACM, Citeseer DBpedia, and (b) liaise with all relevant communities (PSI, DBpedia, LOD, W3C SWEO etc.) to leverage and outreach to additional stakeholders and multipliers. CNR will provide technical support for synchronizing content of the OpenAIRE Information Space with LOD services and vice versa, in the case content can be moved from enriched LOD representation to the OpenAIRE Information Space.

LEADER: UBONN
PARTICIPANTS: ARC, CNR

TASK 8.3: RESEARCH IMPACT SERVICES

The task will focus on the realization of general-purpose services for measurement of research impact w.r.t. a “research initiative”. Such services will identify relationships between publications/datasets and a given “research initiative” (e.g. research infrastructures) by offering: (i) inference by mining functionality and (ii) end-user claim functionality (i.e. endusers declare links). Services will also offer UIs for visualizing statistics and measuring research impact over time. As a use-case, the task will focus on the development of pilots with selected National funding agencies (e.g. NWO, DFG, NCBR) and infrastructure initiatives (e.g. EGI, PRACE) in order to serve them with the OpenAIRE research impact suit of services. ARC and CNR will: (a) select funding agencies with the help of the NOADs, (b) offer technical support for interoperability with funding agencies data sources in order to collect project information from them, and (c) identify the data model changes required to support the integration.

LEADER: ARC
PARTICIPANTS: CNR

TASK 8.4: Data flows and dynamics monitoring services

These services will be used to monitor overtime all data flows in the OpenAIRE infrastructure, in order to verify the expected quality of a newer version of the Information Space before making it available to the public via portal and APIs. To this aim, the services will evaluate and certificate data flows and dynamics over time, since the last Information Space was released. Examples of Information Space certification elements may regard “Expected Information Space variance”: e.g. the percentage of OA vs non-OA material should not exceed a given ratio; the number of inferred relationships can increase but should not have down-peaks of 10% with respect to previous status; different harvestings of the same data sources should increase in the number of collected objects. Data curators will be able to: (a) configure the services to verify specific data flows and dynamics w.r.t. given measures and thresholds, (b) be consequently notified of misbehaviors or technical issues in order to fix them or, if tolerable, publish the Information Space as is; (c) have access to an history of “status certificates” of current and past Information Spaces. Data curators will also be able to configure and follow the overall monitoring activities via user interfaces, which will offer a graphical representation of the activities. CNR will be in charge of the design and development of the service, while UNIBI will serve the requirements of data curators.

LEADER: CNR
PARTICIPANTS: UNIBI

TASK 8.5: USAGE STATISTIC SERVICES

This task has the twofold aim of: (a) Aligning policies and standards: allowing data sources used for research dissemination (e.g. publication and data repositories, CRIS systems) to align their policies and share standards for gathering and sharing usage data and stats, (b) Collecting and analyzingusage data to produce metrics: realizing OpenAIRE infrastructure workflows and services to aggregate usage data and stats from heterogeneous data sources, investigate usage data metrics, and integrate usage statistics in the OpenAIRE portal. Studies include: guidelines for exporting usage data and stats (ARC, UMINHO, Jisc); legal frameworks for usage data sharing (Jisc, UMINHO); examining aggregated usage data in the light of established metrics (e.g., citation analysis); study and integrate alternative types of usage data related to researcher social behavior (altmetrics). Developments include: tools for repository platforms (e.g. DSpace) to export/import usage data (UMINHO); large-scale analytics infrastructural services to process the aggregated data (ARC, UNIBI); APIs (ARC, UNIBI) so that different providers can study, pilot and produce different types of metrics.

LEADER: UNIBI
PARTICIPANTS: ARC, UMINHO, COUPERIN, JISC
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