scholarly journals Global open data management in metabolomics

2017 ◽  
Vol 36 ◽  
pp. 58-63 ◽  
Author(s):  
Kenneth Haug ◽  
Reza M Salek ◽  
Christoph Steinbeck
Keyword(s):  
Data Management ◽  
Open Data

scholarly journals The Open Data Challenge: An Analysis of 124,000 Data Availability Statements and an Ironic Lesson about Data Management Plans

2020 ◽  
Vol 2 (4) ◽  
pp. 554-568
Author(s):  
Chris Graf ◽  
Dave Flanagan ◽  
Lisa Wylie ◽  
Deirdre Silver
Keyword(s):  
Machine Learning ◽  
Data Management ◽  
Open Data ◽  
Research Data ◽  
Data Availability ◽  
Policy Changes ◽  
Management Plans ◽  
Trends Over Time ◽  
New Research ◽  
Over Time

Data availability statements can provide useful information about how researchers actually share research data. We used unsupervised machine learning to analyze 124,000 data availability statements submitted by research authors to 176 Wiley journals between 2013 and 2019. We categorized the data availability statements, and looked at trends over time. We found expected increases in the number of data availability statements submitted over time, and marked increases that correlate with policy changes made by journals. Our open data challenge becomes to use what we have learned to present researchers with relevant and easy options that help them to share and make an impact with new research data.

scholarly journals Employing GIS towards shaping a smart and sustainable future: a brief policy survey of global and Taiwan’s efforts

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Chih-Wei Chen ◽  
Ching-Yi Lin ◽  
Chine-Hung Tung ◽  
Hsiung-Ming Liao ◽  
Jr-Jie Jang ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Data Management ◽  
Cyber Security ◽  
Open Data ◽  
Geographic Information ◽  
The Sustainable Development ◽  
Digital Era ◽  
Sustainable Future ◽  
Strategic Policies

<p><strong>Abstract.</strong> Since UN announced 17 SDGs in 2015, many countries around the world have been endeavouring to promote SDGs towards building a sustainable future. Given the disparity of the regional development, national government is suggested to establish localised sustainable vision. Drawing on UN SDGs with targets and corresponding indicators, meanwhile considering local circumstances and sustainable vision, government further seeks to establish localised SDGs with related targets and indicators. Meanwhile, under the digital era, digital technologies have been extensively employed as the smart tool in many fields nowadays, and Geographic Information System (GIS) has been developed as the platform to visualise the SDGs progress in UN and many countries. On the above basis, this paper further demonstrates Taiwan’s efforts to establish localised SDGs, and develop National Geographic Information System (NGIS) to implement the sustainable development in Taiwan, monitor the SDGs progress, and provide feedback to policymakers to further make strategic policies in a top-down approach, meanwhile develop Community Geographic Information System (CGIS) to encourage stakeholders and citizens to harness the concept of CGIS to proactively create and tell their own stories and promote Regional Revitalisation policy in a bottom-up approach. Moreover, GIS could not function well without appropriate data management including massive data and open data policy, well-built digital infrastructure, as well as the selected “right data” and cyber security. Hence, with appropriate data management, GIS as a smart tool could facilitate the promotion and implementation of SDGs in an intuitive manner towards shaping a smart and sustainable future.</p>

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.

An Advanced Open Data Platform for Integrated Support of Data Management, Distribution, and Analysis

2021 ◽  
Author(s):  
Heesun Won ◽  
Minh Chau Nguyen ◽  
Myeong-Seon Gil ◽  
Yang-Sae Moon
Keyword(s):  
Data Management ◽  
Open Data ◽  
Data Platform

scholarly journals Changing civil servants’ behaviour concerning the opening of governmental data: evaluating the effect of a game by comparing civil servants’ intentions before and after a game intervention

2020 ◽  
pp. 002085232096221
Author(s):  
Fernando Kleiman ◽  
Marijn Janssen ◽  
Sebastiaan Meijer ◽  
Sylvia JT Jansen
Keyword(s):  
Data Management ◽  
Civic Participation ◽  
Public Policies ◽  
Open Data ◽  
Civil Servants ◽  
Behavioural Intention ◽  
Privacy And Security ◽  
Economic Opportunities ◽  
Before And After ◽  
Game Intervention

Open data policies are increasingly being adopted by governments. However, civil servants find it challenging to comply with open data policies. Gaming can help civil servants to practise opening data and can change their behaviour to support the opening of more data. In this article, the effect of playing a game is evaluated in an experiment in which several factors that influence the opening of data are compared before and after the game. The benefits appeared in unexpected ways and areas. Data management, privacy and security knowledge was transferred using the game, the perception of benefits showed significant changes, and behavioural intention was positively affected. Points for practitioners Civil servants’ behaviour influences how public policies are enacted. The release of open data by governments is related by many as crucial for increasing public transparency and civic participation, and generating new economic opportunities. Games can influence the attitude of civil servants and, consequently, change governments’ decisions. Transferring knowledge and providing insights from new experiences can influence civil servants’ attitudes to open data. Moreover, governments can use games to influence civil servants’ attitudes.

Semantically Enriched Task and Workflow Automation in Crowdsourcing for Linked Data Management

2014 ◽  
Vol 08 (04) ◽  
pp. 415-439 ◽  
Author(s):  
Amna Basharat ◽  
I. Budak Arpinar ◽  
Shima Dastgheib ◽  
Ugur Kursuncu ◽  
Krys Kochut ◽  
...  
Keyword(s):  
Data Management ◽  
Linked Data ◽  
Critical Role ◽  
Workflow Management ◽  
Open Data ◽  
Control Flow ◽  
Human Computation ◽  
Amazon Mechanical Turk ◽  
Data Sets ◽  
Task Specification

Crowdsourcing is one of the new emerging paradigms to exploit the notion of human-computation for harvesting and processing complex heterogenous data to produce insight and actionable knowledge. Crowdsourcing is task-oriented, and hence specification and management of not only tasks, but also workflows should play a critical role. Crowdsourcing research can still be considered in its infancy. Significant need is felt for crowdsourcing applications to be equipped with well defined task and workflow specifications ranging from simple human-intelligent tasks to more sophisticated and cooperative tasks to handle data and control-flow among these tasks. Addressing this need, we have attempted to devise a generic, flexible and extensible task specification and workflow management mechanism in crowdsourcing. We have contextualized this problem to linked data management as our domain of interest. More specifically, we develop CrowdLink, which utilizes an architecture for automated task specification, generation, publishing and reviewing to engage crowdworkers for verification and creation of triples in the Linked Open Data (LOD) cloud. The LOD incorporates various core data sets in the semantic web, yet is not in full conformance with the guidelines for publishing high quality linked data on the web. Our approach is not only useful in efficiently processing the LOD management tasks, it can also help in enriching and improving quality of mission-critical links in the LOD. We demonstrate usefulness of our approach through various link creation and verification tasks, and workflows using Amazon Mechanical Turk. Experimental evaluation demonstrates promising results not only in terms of ease of task generation, publishing and reviewing, but also in terms of accuracy of the links created, and verified by the crowdworkers.

scholarly journals A Fully Decentralized Triplestore Managed via the Ethereum Blockchain

2021 ◽  
Author(s):  
Damien Graux ◽  
Sina Mahmoodi
Keyword(s):  
Fault Tolerance ◽  
Data Management ◽  
Management Strategies ◽  
Open Data ◽  
High Quality ◽  
Data Infrastructure ◽  
The Public ◽  
Storage And Retrieval ◽  
Web Of Data ◽  
Barrier To Entry

The growing web of data warrants better data management strategies. Data silos are single points of failure and they face availability problems which lead to broken links. Furthermore the dynamic nature of some datasets increases the need for a versioning scheme. In this work, we propose a novel architecture for a linked open data infrastructure, built on open decentralized technologies. IPFS is used for storage and retrieval of data, and the public Ethereum blockchain is used for naming, versioning and storing metadata of datasets. We furthermore exploit two mechanisms for maintaining a collection of relevant, high-quality datasets in a distributed manner in which participants are incentivized. The platform is shown to have a low barrier to entry and censorship-resistance. It benefits from the fault-tolerance of its underlying technologies. Furthermore, we validate the approach by implementing our solution.

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