scholarly journals FAIR and Open Data in Science: The Opportunity for IUPAC

2021 ◽  
Vol 43 (3) ◽  
pp. 12-16
Author(s):  
Ian Bruno ◽  
Simon Coles ◽  
Wolfram Koch ◽  
Leah McEwen ◽  
Fabienne Meyers ◽  
...  
Keyword(s):  
Task Force ◽  
Open Data ◽  
Chemical Data ◽  
Data Standards ◽  
Machine Readable ◽  
Chemistry Community

Abstract At the start of 2020, IUPAC’s Committee on Publications and Cheminformatics Data Standards (CPCDS) formed a Task Force to propose guidelines for the dissemination and sharing of machine-readable chemical data. These guidelines would be for IUPAC to adopt internally and recommend to the wider chemistry community.

scholarly journals NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany

2020 ◽  
Vol 6 ◽  
Author(s):  
Christoph Steinbeck ◽  
Oliver Koepler ◽  
Felix Bach ◽  
Sonja Herres-Pawlis ◽  
Nicole Jung ◽  
...  
Keyword(s):  
Data Management ◽  
Data Science ◽  
Open Data ◽  
Research Data ◽  
Data Standards ◽  
Data Repositories ◽  
Data Infrastructure ◽  
Research Data Management ◽  
Wide Range ◽  
Chemistry Community

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

scholarly journals The ADRIREEF database: a comprehensive collection of natural/artificial reefs and wrecks in the Adriatic Sea

2021 ◽  
Vol 13 (5) ◽  
pp. 1905-1923
Author(s):  
Annalisa Minelli ◽  
Carmen Ferrà ◽  
Alessandra Spagnolo ◽  
Martina Scanu ◽  
Anna Nora Tassetti ◽  
...  
Keyword(s):  
Literature Review ◽  
Adriatic Sea ◽  
Three Dimensional ◽  
Open Data ◽  
Artificial Reefs ◽  
Network Data ◽  
Comprehensive Collection ◽  
Blue Economy ◽  
Data Ingestion ◽  
Machine Readable

Abstract. The paper presents a database of information on wrecks, natural and artificial reefs located in the Adriatic Sea, collected within the framework of the Interreg Italy–Croatia project ADRIREEF – Innovative exploitation of Adriatic Reefs in order to strengthen Blue Economy. The data collection lasted more than 1 year and included three surveys and a wide literature review. After being collected, data were harmonized and, where possible, made machine-readable. Moreover, data were widely metadated, published in a WebGIS (https://adrireef.github.io/sandbox3/, last access: 3 May 2021), and shared as open data in EMODnet (European Marine Observation and Data Network) Data Ingestion Portal through the SEANOE repository (Ferrà et al., 2020; https://doi.org/10.17882/74880). The database is composed of 285 three-dimensional records, each one described by 51 attributes. Parameters are clustered in four main groups: identification, reef description, site description, and management/exploitation information. Available literature (scientific and/or grey) was also included in the database and linked to the corresponding site.

scholarly journals CNSA: a data repository for archiving omics data

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Xueqin Guo ◽  
Fengzhen Chen ◽  
Fei Gao ◽  
Ling Li ◽  
Ke Liu ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Analytical Data ◽  
Academic Research ◽  
Open Data ◽  
Data Repository ◽  
Free Access ◽  
Omics Data ◽  
Sequencing Data ◽  
Data Standards ◽  
Sample Information

Abstract With the application and development of high-throughput sequencing technology in life and health sciences, massive multi-omics data brings the problem of efficient management and utilization. Database development and biocuration are the prerequisites for the reuse of these big data. Here, relying on China National GeneBank (CNGB), we present CNGB Sequence Archive (CNSA) for archiving omics data, including raw sequencing data and its further analyzed results which are organized into six objects, namely Project, Sample, Experiment, Run, Assembly and Variation at present. Moreover, CNSA has created a correlation model of living samples, sample information and analytical data on some projects. Both living samples and analytical data are directly correlated with the sample information. From either one, information or data of the other two can be obtained, so that all data can be traced throughout the life cycle from the living sample to the sample information to the analytical data. Complying with the data standards commonly used in the life sciences, CNSA is committed to building a comprehensive and curated data repository for storing, managing and sharing of omics data. We will continue to improve the data standards and provide free access to open-data resources for worldwide scientific communities to support academic research and the bio-industry. Database URL: https://db.cngb.org/cnsa/.

scholarly journals OPEN SCIENCE: Where are we? How did we get here? Where to we go from here?

2018 ◽  
Author(s):  
Maryrose Franko
Keyword(s):  
Open Data ◽  
Open Science ◽  
Data Formats ◽  
Informed Decisions ◽  
Scientific Innovation ◽  
Readable Form ◽  
Machine Readable ◽  
The Impact ◽  
Machine Readable Form

The mission of nonprofit funders dictates that research resulting from our funding be freely accessed by our patients and families to help make informed decisions about care, and by our boards and donors to be able to evaluate the impact of our funding. But it is equally critical to our mission that data resulting from our support be published in a machine-readable form and available in easily accessible and open data formats to enable reuse by other researchers. In addition, as technology evolves the need and the ability to share to all research outputs must evolve with it. Only then can the impact of the research be multiplied - increasing the potential for significant and far-reaching advances and scientific innovation.

scholarly journals Technical Note: The Linked Paleo Data framework – a common tongue for paleoclimatology

2015 ◽  
Vol 11 (5) ◽  
pp. 4309-4327
Author(s):  
N. P. McKay ◽  
J. Emile-Geay
Keyword(s):  
Open Data ◽  
Technical Note ◽  
Structured Data ◽  
Data Standards ◽  
Knowledge Representations ◽  
Standard Data ◽  
Data Framework ◽  
Online Databases ◽  
Scientific Endeavor ◽  
Paleoclimate Data

Abstract. Paleoclimatology is a highly collaborative scientific endeavor, increasingly reliant on online databases for data sharing. Yet, there is currently no universal way to describe, store and share paleoclimate data: in other words, no standard. Data standards are often regarded by scientists as mere technicalities, though they underlie much scientific and technological innovation, as well as facilitating collaborations between research groups. In this article, we propose a preliminary data standard for paleoclimate data, general enough to accommodate all the proxy and measurement types encountered in a large international collaboration (PAGES2K). We also introduce a vehicle for such structured data (Linked Paleo Data, or LiPD), leveraging recent advances in knowledge representations (Linked Open Data). The LiPD framework enables quick querying and extraction, and we expect that it will facilitate the writing of open-source, community codes to access, analyze, model and visualize paleoclimate observations. We welcome community feedback on this standard, and encourage paleoclimatologists to experiment with the format for their own purposes.

scholarly journals OPTIMETA – Strengthening the Open Access publishing system through open citations and spatiotemporal metadata 

2021 ◽  
Vol 7 ◽  
Author(s):  
Christian Hauschke ◽  
Daniel Nüst ◽  
Anette Cordts ◽  
Svantje Lilienthal
Keyword(s):  
Open Access ◽  
Open Data ◽  
Data Sources ◽  
Needs Analysis ◽  
Open Access Publishing ◽  
Citation Networks ◽  
Temporal Properties ◽  
Open Access Journals ◽  
Key Stakeholders ◽  
Machine Readable

The BMBF project OPTIMETA aims to strengthen the Open Access publishing system by connecting open citations and spatiotemporal metadata from open access journals with openly accessible data sources. For this purpose, we will extend Open Journal Systems (OJS) to give it functionalities for collecting and distributing open data by developing two OJS plugins for capturing citation networks and articles' spatial and temporal properties as machine-readable and accessible metadata. We will ensure the target group-orientated design of the plugins by performing a comprehensive needs analysis for key stakeholders: the editors or operators of OA journals and the researchers, as authors and readers of articles. The developments will be designed and tested in cooperation with several independent journals and OA publishers. Overall, OPTIMETA supports the attraction of independent OA journals as publication venues by substantially improving the discoverability and visibility of OA publications through enrichment and interlinking of article metadata.

scholarly journals Digital cultural heritage standards: from silo to semantic web

AI & Society ◽  
2022 ◽  
Author(s):  
Brenda O’Neill ◽  
Larry Stapleton
Keyword(s):  
Semantic Web ◽  
Cultural Heritage ◽  
Description Logic ◽  
Open Data ◽  
The United States ◽  
Interdisciplinary Teams ◽  
Academic Disciplines ◽  
Institutional Knowledge ◽  
Digital Cultural Heritage ◽  
Machine Readable

AbstractThis paper is a survey of standards being used in the domain of digital cultural heritage with focus on the Metadata Encoding and Transmission Standard (METS) created by the Library of Congress in the United States of America. The process of digitization of cultural heritage requires silo breaking in a number of areas—one area is that of academic disciplines to enable the performance of rich interdisciplinary work. This lays the foundation for the emancipation of the second form of silo which are the silos of knowledge, both traditional and born digital, held in individual institutions, such as galleries, libraries, archives and museums. Disciplinary silo breaking is the key to unlocking these institutional knowledge silos. Interdisciplinary teams, such as developers and librarians, work together to make the data accessible as open data on the “semantic web”. Description logic is the area of mathematics which underpins many ontology building applications today. Creating these ontologies requires a human–machine symbiosis. Currently in the cultural heritage domain, the institutions’ role is that of provider of this  open data to the national aggregator which in turn can make the data available to the trans-European aggregator known as Europeana. Current ingests to the aggregators are in the form of machine readable cataloguing metadata which is limited in the richness it provides to disparate object descriptions. METS can provide this richness.

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