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This Data Management Plan outlines a comprehensive strategy for handling, storing, and sharing of data generated by digitisation projects of the herbarium at Meise Botanic Garden with Index Herbarium code BR. Its purpose is to establish clear guidelines for both staff and external users, specifying the terms governing data usage and storage. It aims to prioritise the FAIR principles (Findable, Accessible, Interoperable and Reusable), ensure responsible data management, facilitate long-term preservation, uphold legal and ethical obligations, all while aligning with the research excellence mission of Meise Botanic Garden. This plan serves as a guiding document to effectively and efficiently achieve these goals.

This Data Management Plan outlines a comprehensive strategy for handling, storing, and sharing of data generated by digitisation projects of the herbarium at Meise Botanic Garden with Index Herbarium code BR. Its purpose is to establish clear guidelines for both staff and external users, specifying the terms governing data usage and storage. It aims to prioritise the FAIR principles (Findable, Accessible, Interoperable and Reusable), ensure responsible data management, facilitate long-term preservation, uphold legal and ethical obligations, all while aligning with the research excellence mission of Meise Botanic Garden. This plan serves as a guiding document to effectively and efficiently achieve these goals. [ABSTRACT FROM AUTHOR]

A study on the feasibility of a national open data policy in Zimbabwe was done to document open government data globally and in Zimbabwe. The study showcases the benefits of open government data and the opportunities and challenges toward the development of a national open data policy. Web content analysis and document analysis were used to collect data concerning the readiness of the country in implementing open data activities. The open data barometer was used to gather qualitative data which is essential in assessing the preparedness of the country in opening up government and research data. Content analysis was used to analyse the data which was presented thematically based on the objectives of the study. The findings indicated that the Government of Zimbabwe has endorsed a couple of open data frameworks though some projects are done by non-governmental organizations. The major challenge is implementation of these conventions and commitment to make the data accessible. The results indicated that open data must be made available and accessible within Zimbabwe as a matter of national policy. The author recommends the need for advocacy and continuous awareness creation among the stakeholders so that a national open data policy can be crafted and enacted. The enactment of a national open data policy would guide the use of and access to government data and research data which is valuable in research.

A study was conducted on the role of research institute libraries in supporting open data research policies to improve scientific communication. The study aims to determine the role of libraries in open data research policies to improve scientific communication, and determine the role of libraries in relation to the open data research movement in building scientific communication. The research was conducted using the narrative review method, which is research that is carried out looking for articles related to the study of the role of research institutes libraries in open data research policies to improve scientific communication. namely data management plans and research data sharing processes, ensuring the data can be accessed, storing data in repositories and ensuring data can be accessed within a certain period of time. Libraries are the pioneers of the open data research movement by providing consultancy services for data analysis, research data mining, data curation services, data analysis and visualization, and saving research data over a long period of time. The main support provided by the library in building scientific communication is to create meta data and store data in repositories. Provide training in the management and storage of research data for researchers with the aim that the resulting research data can be used and disseminated for further research

The conversion of published data by government to a value and social effect is not done automatically and requires a number of actors with different functions that by activating and connecting them with each other, we can use data. The sum of these actors, stakeholders and their functions is called the Open Government Data Ecosystem. This study aims to understand the ecosystem of open government data and analysis of selected open government ecosystem models is formed. Present study is an exploratory study that seeks to analyze international models of open government data ecosystem, and identify and monitor the elements and components of the open government data ecosystem. Open government data ecosystem models were redefined and its contents were extracted by content analysis method and then compared and evaluated. Units in this study are open government data ecosystem models and sampling is targeted sampling. In the first stage, 36 models were identified by searching and reviewing the models of open government data ecosystems. Finally, by studying these models and identifying the similarities and aggregating of some models, based on targeted sampling, the researchers considered 12 models of open government data ecosystem and by examining them they extracted the data and information from these models. The reason for choosing these 12 models is their reputation, influence, comprehensiveness and authority. By examining existing models, it has become clear that there is still no comprehensive model of an open government data ecosystem that could be the basis for developing an open government data policy. Summarizing or generalizing, paying attention to a part of the ecosystem, using a cyclic or value chain approach instead of ecosystems approach, and some of the models are an experience or specific area of the characteristics of ecosystem models.

The purpose of this paper is to explore current data management training needs and practices for Belmont Forum member agencies and researchers to inform a Toolkit. Fourteen Belmont Forum affiliated individuals were interviewed following a predetermined set of questions to create data curation profiles of their funded work. The data curation profile questionnaire includes questions related to data management, storage, stakeholders, costs, training, and credentials. The interview findings highlight gaps in existing knowledge of data management theory and practice that could impact data re-use. Results of these interviews were used to populate a Toolkit of data management training and effective practice resources specifically developed to train Belmont Forum grant awardees. The results also highlight some attitudes and behaviours of current scientists, researchers, and agency representatives, and the impact of the implementation of data management plans on the open science movement.

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The Open Science (OS) agenda has potentially massive cultural, organizational and infrastructural consequences. Ambitions for OS-driven policies have proliferated, within which researchers are expected to publish their scientific data. Significant research has been devoted to studying the issues associated with managing Open Research Data. Digital curation, as it is typically known, seeks to assess data management issues to ensure its long-term value and encourage secondary use. Hitherto, relatively little interest has been shown in examining the immense gap that exists between the OS grand vision and researchers' actual data practices. Our specific contribution is to examine research data practices before systematic attempts at curation are made. We suggest that interdisciplinary ethnographically-driven contexts offer a perspicuous opportunity to understand the Data Curation and Research Data Management issues that can problematize uptake. These relate to obvious discrepancies between Open Research Data policies and subject-specific research practices and needs. Not least, it opens up questions about how data is constituted in different disciplinary and interdisciplinary contexts. We present a detailed empirical account of interdisciplinary ethnographically-driven research contexts in order to clarify critical aspects of the OS agenda and how to realize its benefits, highlighting three gaps: between policy and practice, in knowledge, and in tool use and development. [ABSTRACT FROM AUTHOR]

A number of countries around the world have embraced the open science agenda. However, in some cases, existing legislative frameworks in most countries typically do not allow much openness of data and science. Botswana is an example of such countries. The absence of legislative framework poses a challenge to librarians, researchers and policy makers with regard to data sharing. This has derailed the country’s development in terms of innovation and creativity. This issue has prompted different stakeholders to come together to work towards changing the current systems and regulatory frameworks in relation to open science and data management. The Botswana Open Data Open Science (ODOS) national committee was established in 2017 by different stakeholders being public bodies, business communities, information professionals and research communities to develop an open data open science policy that would enable data sharing and openness in science within the country. The purpose of this paper is to share the strategies used to establish inclusive interactions and engagement between stakeholders in facilitating the open data readiness implementation in Botswana. Moreover, the paper will highlight challenges encountered and achievement attained through this collaborative effort. [ABSTRACT FROM AUTHOR]

The conversion of published data by government to a value and social effect is not done automatically and requires a number of actors with different functions that by activating and connecting them with each other, we can use data. The sum of these actors, stakeholders and their functions is called the Open Government Data Ecosystem. This study aims to understand the ecosystem of open government data and analysis of selected open government ecosystem models is formed. Present study is an exploratory study that seeks to analyze international models of open government data ecosystem, and identify and monitor the elements and components of the open government data ecosystem. Open government data ecosystem models were redefined and its contents were extracted by content analysis method and then compared and evaluated. Units in this study are open government data ecosystem models and sampling is targeted sampling. In the first stage, 36 models were identified by searching and reviewing the models of open government data ecosystems. Finally, by studying these models and identifying the similarities and aggregating of some models, based on targeted sampling, the researchers considered 12 models of open government data ecosystem and by examining them they extracted the data and information from these models. The reason for choosing these 12 models is their reputation, influence, comprehensiveness and authority. By examining existing models, it has become clear that there is still no comprehensive model of an open government data ecosystem that could be the basis for developing an open government data policy. Summarizing or generalizing, paying attention to a part of the ecosystem, using a cyclic or value chain approach instead of ecosystems approach, and some of the models are an experience or specific area of the characteristics of ecosystem models. [ABSTRACT FROM AUTHOR]

This paper provides an overview of Bulgaria’s policy on open data by using the framework of a novel Open Data stage model, showing that the country is still at the first stage of opening data. We also present a detailed overview of the data landscape of the public sector in the country and outline the first milestones and successes in its efforts to publish some of that data for reuse. A complete data audit reveals persistent technological and cultural barriers to publishing public sector information but also outlines the potential of doing so. The paper summarizes the limited knowledge about the actual benefits of open data and proposes moving beyond anecdotal evidence and usage metrics toward a more complete impact evaluation. [ABSTRACT FROM PUBLISHER]

A study on the feasibility of a national open data policy in Zimbabwe was done to document open government data globally and in Zimbabwe. The study showcases the benefits of open government data and the opportunities and challenges toward the development of a national open data policy. Web content analysis and document analysis were used to collect data concerning the readiness of the country in implementing open data activities. The open data barometer was used to gather qualitative data which is essential in assessing the preparedness of the country in opening up government and research data. Content analysis was used to analyse the data which was presented thematically based on the objectives of the study. The findings indicated that the Government of Zimbabwe has endorsed a couple of open data frameworks though some projects are done by non-governmental organizations. The major challenge is implementation of these conventions and commitment to make the data accessible. The results indicated that open data must be made available and accessible within Zimbabwe as a matter of national policy. The author recommends the need for advocacy and continuous awareness creation among the stakeholders so that a national open data policy can be crafted and enacted. The enactment of a national open data policy would guide the use of and access to government data and research data which is valuable in research., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chigwada.)

The broad dissemination of open data policies for Big Earth data leads to a diversification of users. The literacy in data and data handling differs for each user group, resulting in different needs and requirements. In addition, the development of cloud-based data systems challenges traditional workflows of all users. In order to tailor new cloud-based data systems for Earth data users, it is of utmost importance to obtain a better understanding of users in terms of the type of data they explore, the applications they need the data for, the way they access and process data, and the challenges they face. This is an indispensable prerequisite to ensure an increased uptake of Big Earth data in the future. In order to get a better insight in the requirements and challenges of users coping with Big Earth data, we run a comprehensive web-based user survey. Our results, inclined to users of Big Earth data in Europe and the North American continent, reveal that a majority of survey respondents still download copies of data onto their local machine and handle and process data locally with a combination of programming and desktop-based software. However, survey respondents are facing severe problems related to the growing data volumes, the data heterogeneity and the limited processing capacities for their demanding applications. Thus, they show a specific interest in using cloud-based data services in the near future but express the need for an easier data discovery and the interoperability of data systems. Based on the survey findings, we draw a set of recommendations to make Big Earth data more FAIR (findable, accessible, interoperable and re-useable). • User requirements are a driving force of the development of emerging cloud-based systems for Big Earth data. • Growing data volume and limited processing capacity top Big Earth data challenges. • Cloud-based data systems are not broadly used but attract user's interest and are preferred over 'user-centric' platforms. • The formation of a global cloud consortium can help to make the Big Earth data landscape more FAIR in the future. [ABSTRACT FROM AUTHOR]

• A new Data Openness in Air Quality (DOAQ) framework with 3 tiers and 23 open data principles is established. • Assessments of status and development of air quality openness of top 50 smart cities are conducted via the DOAQ approach. • Strong correlations between newly developed DOAQ index and other smart city indices or socioeconomic attributes are obtained. • Factors that constitute to the relatively poor performance of individual smart cities are identified and explained. • Good practices of promoting sustainability and air quality openness through public engagement are presented. Data Openness is considered as an indispensable component for scientific innovation, community engagement and smart city development. In this study, a Data Openness in Air Quality (DOAQ) framework that consists of 3 tiers with a total of 23 open data principles was established to assess and monitor the status and development of data sharing, release and centralization of air quality information in the top 50 smart cities (Top50SC) around the world. The DOAQ utilizes additive formulas with predefined coefficients to obtain scores in each tier, thus reflecting the relative importance on data availability and visibility of different air quality data. The scores of DOAQ were compared with the smart cities scorings from Eden Strategy Institute and ONG&ONG Pte Ltd. (2018), and other socioeconomic attributes (i.e., social, political and humane) within the current study. Strong correlations (i.e., 0.4−0.6) among these indices implicate that the status of air quality reporting could be a good proxy to gauge the environmental data openness in a city. Lastly, good practices (e.g., apps and air quality forecasts), essential criteria and directions for future smart city development on air quality reporting were summarized, with the aim of laying down practical and efficient guidelines for individual smart city that desires to seek for improvements in air quality data openness. [ABSTRACT FROM AUTHOR]