Information Inference in Scholarly Communication Infrastructures: The OpenAIREplus Project Experience

Digital Libraries for Open Knowledge

Kokogiannaki

et al. 2019

Self Cite

Despite the hype, the effective implementation of Open Science is hindered by several cultural and technical barriers. Researchers embraced digital science, use "digital laboratories" (e.g. research infrastructures, thematic services) to conduct their research and publish research data, but practices and tools are still far from achieving the expectations of transparency and reproducibility of Open Science. The places where science is performed and the places where science is published are still regarded as different realms. Publishing is still a post-experimental, tedious, manual process, too often limited to articles, in some contexts semantically linked to datasets, rarely to software, generally disregarding digital representations of experiments. In this work we present the OpenAIRE Research Community Dashboard (RCD), designed to overcome some of these barriers for a given research community, minimizing the technical efforts and without renouncing any of the community services or practices. The RCD flanks digital laboratories of research communities with scholarly communication tools for discovering, publishing, and monitoring interlinked scientific products such as literature, datasets, and software. The benefits of the RCD are show-cased by means of two real-case scenarios: the European Marine Science community and the European Plate Observing System (EPOS) research infrastructure.

Section: The Openaire Infrastructurementioning

confidence: 99%

The OpenAIRE Research Community Dashboard: On Blending Scientific Workflows and Scientific Publishing

Baglioni

Digital Libraries for Open Knowledge

Kokogiannaki

et al. 2019

Self Cite

“…The OpenAIRE information inference system (IIS) is based on an instantiation of the Information Inference Framework (IIF) [1]. The IIS is responsible for enriching the ISG with new information produced by various types of data mining algorithms.…”

Section: Information Inference Workflowmentioning

confidence: 99%

“…In order to help repository managers to integrate their data with OpenAIRE, the guidelines (https://guidelines.openaire.eu) describe how to expose such information (publications, datasets, CRIS metadata) via the OAI-PMH protocol. Relationships between objects are collected from the data sources, but also automatically detected by inference algorithms [1] and added by users, who can insert links between publications, datasets and projects via the claiming procedure available from the OpenAIRE web portal. The Information Space is available for human and machine consumption via the OpenAIRE web portal and different kinds of APIs.…”

Section: Introductionmentioning

confidence: 99%

The OpenAIRE Workflows for Data Management

Atzori

Communications in Computer and Information Science

Manghi

et al. 2017

Self Cite

Abstract. The OpenAIRE initiative is the point of reference for Open Access in Europe and aims at the creation of an e-Infrastructure for the free flow, access, sharing, and re-use of research outcomes, services and processes for the advancement of research and the dissemination of scientific knowledge. OpenAIRE makes openly accessible a rich Information Space Graph (ISG) where products of the research life-cycle (e.g. publications, datasets, projects) are semantically linked to each other. Such an information space graph is constructed by a set of autonomic (orchestrated) workflows operating in a regimen of continuous data integration. This paper discusses the principal workflows operated by the Open-AIRE technical infrastructure in its different functional areas and provides the reader with the extent of the several challenges faced and the solutions realized. IntroductionThe OpenAIRE initiative is the point of reference for Open Access in Europe [3] [4]. Its mission is to foster an Open Science e-Infrastructure that links people, ideas and resources for the free flow, access, sharing, and re-use of research outcomes, services and processes for the advancement of research and the dissemination of scientific knowledge. OpenAIRE operates an open, collaborative, service oriented infrastructure that supports (i) the realization of a pan-European network for the definition, promotion and implementation of shared interoperability guidelines and best practices for managing, sharing, re-using, and preserving research outcomes of different typologies; (ii) the promotion of Open Science policies and practices at all stages of the research life-cycle and across research communities belonging to different application domains and geographical areas; (iii) the provision of measurements of the impact of Open Science and the return of investment of national and international funding agencies; (iv) the development and operation of a technical infrastructure supporting services for the discovery of and access to research outcomes via a centralized entry point, where research outcomes are enriched with contextual information via links to objects relevant to the research life-cycle. This paper focuses on the workflows operated by the OpenAIRE technical infrastructure for the management of the OpenAIRE information space. The

“…• Enrichment (information inference sub-system): publication full-texts are collected and processed by text mining services [12] capable of inferring new property values or new relationships between objects. In order to give visibility to the contributing data sources, OpenAIRE keeps provenance information about each piece of aggregated information.…”

Section: Figure 1 -The Openaire Data Modelmentioning

confidence: 99%

Realizing a Scalable and History-Aware Literature Broker Service for OpenAIRE

Manghi

Atzori

Communications in Computer and Information Science

et al. 2017

Self Cite

Abstract. The OpenAIRE infrastructure is the point of reference for Open Science in Europe. Its services populate and provide access to a graph of objects relative to publications, datasets, people, organizations, projects, and funders aggregated from a variety of data sources, such as institutional repositories, data archives, journals, and CRIS systems. Not only, objects in the graph are harmonized to achieve semantic homogeneity, de-duplicated and merged, and enriched by inference with missing properties and/or relationships. The OpenAIRE Literature Broker Service is designed to offer subscription and notification functionalities for institutional repositories to: (i) learn about publication objects in OpenAIRE that do not appear in their collection but may be pertinent to it, and (ii) learn about extra properties or relationships relative to publication objects in their collection. Due to the high variability of the information space the following problems may arise: (i) subscriptions may vary over time to adapt to information space evolution, (ii) repository managers need to be able to quickly test their configurations before activating them, (iii) notifications may be redundant, and (iv) notifications may be very large over time. This paper presents the data model and software architecture of the OLBS, specifically designed to address these issues.