Editors : José María Cavanillas, Edward Curry, Wolfgang Wahlster
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements.
And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy.
Authors : Joachim Schöpfel, Hélène Prost,Violaine Rebouillat
The paper provides an overview of recent research and publications on the integration of research data in Current Research Information Systems (CRIS) and addresses three related issues, i.e. the object of evaluation, identifier schemes and conservation.
Our focus is on social sciences and humanities. As research data gradually become a crucial topic of scientific communication and evaluation, current research information systems must be able to consider and manage the great variety and granularity levels of data as sources and results of scientific research.
More empirical and moreover conceptual work is needed to increase our understanding of the reality of research data and the way they can and should be used for the needs and objectives of research evaluation.
The paper contributes to the debate on the evaluation of research data, especially in the environment of open science and open data, and will be helpful in implementing CRIS and research data policies.
Why has the rise of the Internet – which drastically reduces the cost of distributing information – coincided with drastic increases in the prices that academic libraries pay for access to scholarly journals?
This study argues that libraries are trapped in a collective action dilemma as defined by economist Mancur Olson in The Logic of Collective Action: Public Goods and the Theory of Groups.
To truly reduce their costs, librarians would have to build a shared online collection of scholarly resources jointly managed by the academic community as a whole, but individual academic institutions lack the private incentives necessary to invest in a shared collection.
Thus, the management of online scholarly journals has been largely outsourced to publishers who have developed monopoly powers that allow them to increase subscription prices faster than the rate of inflation.
Many librarians consider the Open Access Movement the best response to increased subscription costs, but the current strategies employed to achieve Open Access also are undermined by collective action dilemmas. In conclusion, some alternative strategies are proposed.
Authors : Andra Waagmeester, Martina Kutmon, Anders Riutta, Ryan Miller, Egon L. Willighagen, Chris T. Evelo , Alexander R. Pico
The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data.
The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org.
Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries.
In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web.
WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development.
We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.
In this article we argue that the current endeavors to achieve open access in scientific
literature require a discussion about innovation in scholarly publishing and research infrastructure.
Drawing on path dependence theory and addressing different open access (OA) models and recent political endeavors, we argue that academia is once again running the risk of outsourcing the organization of its content.
The characteristics of modern science, i.e., data-intensive, multidisciplinary, open, and heavily dependent on Internet technologies, entail the creation of a linked scholarly record that is online and open.
Instrumental in making this vision happen is the development of the next generation of Open Cyber-Scholarly Infrastructures (OCIs), i.e., enablers of an open, evolvable, and extensible scholarly ecosystem.
The paper delineates the evolving scenario of the modern scholarly record and describes the functionality of future OCIs as well as the radical changes in scholarly practices including new reading, learning, and information-seeking practices enabled by OCIs.
While providing the resources and tools that make advanced research possible is a primary mission of academic libraries at large research universities, many other elements also contribute to the success of the research enterprise, such as institutional funding, staffing, labs, and equipment.
This study focuses on U.S. members of the ARL, the Association for Research Libraries. Research success is measured by the total grant funding received by the University, creating an ordered set of categories.
Combining data from the NSF National Center for Science and Engineering Statistics, ARL Statistics, and IPEDS, the primary explanatory factors for research success are examined.
Using linear regression, logistic regression, and the cumulative logit model, the best-fitting models generated by ARL data, NSF data, and the combined data set for both nominal and per capita funding are compared. These models produce the most relevant explanatory variables for research funding, which do not include library-related variables in most cases.