Data Stewardship

The concept of data curation has been a well-known term for scholarly communities. The understanding of data curation itself is necessary for research institutes that manage any kinds of research data set. Yet, research institutions have already set their plan and management to ensure that research data management is going well and supports the objectives of the institutions. For that reason, this paper was made to evaluate the research data cycle and management at several research institutions in Indonesia. The purpose of this paper was also to observe and to analyze how the standards and system have been used at research institutions and how they were effective. Also, it is essential to know how institutions find the term data curation and how it links to the management of research data and its implication to research data. This study used phenomenological method on data curation and how it would affect the performances of research data. The result showed that vital aspects were identified both from the informants and the previous studies. They were the appropriate curation model, data curation regulations, finding problems at the institutions and knowing supported technology, and system for data curation implementation.

The data, information and knowledge are three key concepts and elements of every organization, the big data's effect, the industry 4.0 and the unsuccessful deployments in the data swamps, requires the proper reference in regards data governance and how to create knowlegde. This books explains the lifecycle deployment from data to knowledge, thier policies and a reference practice.

Background. By the 2020 mark, The European Union should have a functional Digital Single Market. One of the policies sustaining the efforts in such endeavour is building a European Data Economy (European Commission 2017a). The aim is to build a common European data space a transformative space even for the information science specialists. Objectives. The study is investigative in nature aiming to extract the traits out of the trends leading to a possible specialisation having a broad scope in searching possible career paths for librarians in data science. Results. A graphical explanatory framework indicating requirements, skills and competencies needed by the librarians to achieve new cross-disciplinary engagements with patrons and the research environment. Methods. Because this study is put in the context of Open Science, and particularly addressing the European Union space, the late developments reflected in the policies and initiatives were taken under scrutiny coupled with relevant European Commission project deliverables. Other studies concentrating on the new roles of the librarians pertaining to data librarian were consulted, and also the body of information gathered around the Open Science Cloud. To couple existing studies' conclusions with the demand in the librarianship, a body of job listings were investigated to find common traits data librarian job descriptions are exposing. To complete a picture, some training facilities were taken into the mix. Debate. Out of many possible roles envisaged for the librarians, there are a few which trigger some focus on the future skills needed to be acquired. These possible scenarios involve data management planning guidance, data stewardship and curation, and data visualisation. Some or all of them might lead to a deep transformation of the librarianship as a craft we were used to up to the Open Science rising tide. The article invites all the information specialists to look into what are the needs to shape up or even to rehash the careers of library and information science specialists.

Translational research applies findings from basic science to enhance human health and well-being. In translational research projects, academia and industry work together to improve healthcare, often through public-private partnerships. This “translation” is often not easy, because it means that the so-called “valley of death” will need to be crossed: many interesting findings from fundamental research do not result in new treatments, diagnostics and prevention. To cross the valley of death, fundamental researchers need to collaborate with clinical researchers and with industry so that promising results can be implemented in a product. The success of translational research projects often does not depend only on the fundamental science and the applied science, but also on the informatics needed to connect everything: the translational research informatics. This informatics, which includes data management, data stewardship and data governance, enables researchers to store and analyze their ‘big data’ in a meaningful way, and enable application in the clinic. The author has worked on the information technology infrastructure for several translational research projects in oncology for the past nine years, and presents his lessons learned in this paper in the form of ten commandments. These commandments are not only useful for the data managers, but for all involved in a translational research project. Some of the commandments deal with topics that are currently in the spotlight, such as machine readability, the FAIR Guiding Principles and the GDPR regulations. Others are mentioned less in the literature, but are just as crucial for the success of a translational research project.

SUMMARY
The significance of data to today’s economy has stimulated ongoing conversations about the regulation and management of data. This is evidenced in the massive amounts of value constantly derived and extracted from it and the severe impacts of its misuse in today’s economy. Our "Exploring the Future of Data Governance in Africa: Data Stewardship, Collaboratives, Trusts and More" paper investigates broadly data stewardship methods, particularly data collaboratives and data trusts efforts and aims to identify the existing challenges, gaps, opportunities and potential recommendations on how to drive this discourse forward.

Librarian data stewards can propose an update of the SA 8000 standard by integrating as a crosscutting requirement the data stewardship for open science based on the European FAIR data guidelines and the GDPR directives for open data, pursuing the Agenda 2030 targets: Target 4.6 “Ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracy”; Target 16.6 “Develop effective, accountable and transparent institutions at all levels”; Target 16.10 “Ensure public access to information and protect fundamental freedoms, in accordance with national legislation and international agreements”. In the evolution of IoT (internet of things) related apps and tools, data driven algorithms are crucial. We therefore speak of IoD (internet of data) as a source for the experimental development of integrated and innovative applications in the environmental and energy services field, the healthcare sector, and also in the context of Smart Cities. For a correct and transparent management of the micro and macrosystemic information flow it becomes essential to share and aggregate different and interoperable sources. The librarian as data steward has the task of promoting cultural change towards shared research, acting on those who produce and reuse data. To this end, it is necessary to facilitate the technology transfer necessary for open science, through the synergy between stakeholders and data producers.

Background:
Connecting currently existing, heterogeneous rare disease (RD) registries would greatly facilitate epidemiological and clinical research. To increase their interoperability, the European Union developed a set of Common Data Elements (CDEs) for RD registries.

Objectives:
To implement the CDEs and the FAIR data principles in the Registry of Vascular Anomalies (VASCA).

Methods:
We created a semantic model for the CDE and transformed this into a Resource Description Framework (RDF) template. The electronic case report forms (eCRF) were mapped to the RDF template and published in a FAIR Data Point (FDP).

Results:
The FAIR VASCA registry was successfully implemented using Castor EDC (Electronic Data Capture) software.

Librarian data stewards can propose an update of the SA 8000 standard by integrating as a crosscutting requirement the data stewardship for open science based on the European FAIR data guidelines and the GDPR directives for open data, pursuing the Agenda 2030 targets: Target 4.6 “Ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracy”; Target 16.6 “Develop effective, accountable and transparent institutions at all levels”; Target 16.10 “Ensure public access to information and protect fundamental freedoms, in accordance with national legislation and international agreements”. In the evolution of IoT (internet of things) related apps and tools, data driven algorithms are crucial. We therefore speak of IoD (internet of data) as a source for the experimental development of integrated and innovative applications in the environmental and energy services field, the healthcare sector, and also in the context of Smart Cities. For a cor...