Category: Data Science Journal Latest Articles

The comparison of absolute geomagnetic instruments is an important component of geomagnetic observation. To promote high quality standards in geomagnetic data acquisition, the International Association of Geomagnetism and Aeronomy (IAGA) organizes an international comparison every two years. In China, this comparison is part of quality control process for geomagnetic observation data, and is organized by the Geomagnetic Network of China (GNC). In this paper, the comparison results from several years are analysed in detail, and some useful information is presented that will help to guide the observatory’s future observation work and improve data quality. In addition, the quality of the absolute observation data of GNC and IAGA is evaluated using a statistical method. This should aid scientists who use these data to understand their research results.

Published on 2019-10-01 09:00:53

Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures. Strengthening international data sharing networks will not only demand advancing technical, legal, and logistical infrastructure for publishing data in open, accessible formats; it will also require recognizing, respecting, and learning to work across diverse data cultures. This essay introduces a heuristic for pursuing richer characterizations of the “data cultures” at play in international, interdisciplinary data sharing. The heuristic prompts cultural analysts to query the contexts of data sharing for a particular discipline, institution, geography, or project at seven scales – the meta, macro, meso, micro, techno, data, and nano. The essay articulates examples of the diverse cultural forces acting upon and interacting with researchers in different communities at each scale. The heuristic we introduce in this essay aims to elicit from researchers the beliefs, values, practices, incentives, and restrictions that impact how they think about and approach data sharing – not in an effort to iron out differences between disciplines, but instead to showcase and affirm the diversity of traditions and modes of analysis that have shaped how data gets collected, organized, and interpreted in diverse settings.

Published on 2019-09-30 08:00:39

Human genomic data are large and complex, and require adequate infrastructure for secure storage and transfer. The NIH and The Wellcome Trust have funded multiple projects on genomic research, including the Human Heredity and Health in Africa (H3Africa) initiative, and data are required to be deposited into the public domain. The European Genome-phenome Archive (EGA) is a repository for sequence and genotype data where the data access is controlled by access committees. Access is determined by a formal application procedure for the purpose of secure storage and distribution, and must be in line with the informed consent of the study participants. H3Africa researchers based in Africa and generating their own data can benefit tremendously from the data sharing capabilities of the internet by using the appropriate technologies. The H3Africa Data Archive is an effort between the H3Africa data generating projects, H3ABioNet and the EGA to store and submit genomic data to public repositories. H3ABioNet maintains the security of the H3Africa Data Archive, ensures ethical security compliance, supports users with data submission and facilitates the data transfer. The goal is to ensure efficient data flow between researchers, the archive and the EGA or other public repositories. To comply with the H3Africa data sharing and release policy, nine months after the data is in secure storage, H3ABioNet converts the data into an XML format ready for submission to EGA. This article describes the infrastructure that has been developed for African human genomic data management.

Published on 2019-09-26 07:32:18

Climatic variables such as rainfall and temperature have nonlinear and non-stationary characteristics such that analysing them using linear methods inconclusive results are found. Ensemble empirical mode decomposition (EEMD) is a data-adaptive method that is best suitable for data with nonlinear and non-stationary characteristics. The average monthly rainfall and temperature data for a selected region in South Africa are decomposed into intrinsic mode functions (IMFs) at different time scales using EEMD. The IMFs exhibit an inter-annual to inter-decadal variability. The influence of climatic oscillations such as El-Niño Southern Oscillation (ENSO) and quasi-biennial oscillation (QBO) is identified. The influence of temperature variability on rainfall is also shown at different time scales. Based on the results obtained, the EEMD method is found to be suitable to identify different oscillations in the rainfall and temperature data.

Published on 2019-09-25 07:30:08

In this paper, we explain our strategy for developing research data management policies at TU Delft. Policies can be important drivers for research institutions in the implementation of good data management practices. As Rans and Jones note (Rans and Jones 2013), “Policies provide clarity of purpose and may help in the framing of roles, responsibilities and requisite actions. They also legitimise making the case for investment”. However, policy development often tends to place the researchers in a passive position, while they are the ones managing research data on a daily basis. Therefore, at TU Delft, we have taken an alternative approach: a policy needs to go hand in hand with practice. The policy development was initiated by the Research Data Services at TU Delft Library, but as the process continued, other stakeholders, such as legal and IT departments, got involved. Finally, the faculty-based Data Stewards have played a key role in leading the consultations with the research community that led to the development of the faculty-specific policies. This allows for disciplinary differences to be reflected in the policies and to create a closer connection between policies and day-to-day research practice. Our primary intention was to keep researchers and research practices at the centre of our strategy for data management. We did not want to introduce and mandate requirements before adequate infrastructure and professional support were available to our research community and before our researchers were themselves willing to discuss formalisation of data management practices.

This paper describes the key steps taken and the most important decisions made during the development of RDM policies at TU Delft.

Published on 2019-09-12 05:46:52

A research data commons can provide researchers with the data and resources necessary to conduct world class research. More than this, a research data commons can be transformational in facilitating change in the way research is conducted, in terms of both research culture and the availability of research data and analytical tools. This paper describes frameworks needed to build a transformational data commons, through examination of the development of the Australian Research Data Commons (ARDC) ARDC was formed in 2018 as part of a 20-year vision to transform Australia’s research culture by enabling access to the digital data and eResearch platforms that can significantly enhance research capacity. ARDC is located within both national and international eResearch ecosystems, and its unique positioning must be understood, alongside the achievements of its three predecessor organisations, to understand the niche from which ARDC aims to provide maximum value and impact. Consideration is given to the challenges inherent in both the current Australian ecosystem and beyond, to articulate ARDC’s focus going forward. The paper concludes with consideration of the international dimension, drawing on discussions around the development of a global data commons.

Published on 2019-09-05 07:45:48

We present a joint effort at Virginia Tech between a research group in the Department of Fish and Wildlife Conservation and Data Services in the University Libraries to improve data management for long-term ecological field research projects in the Florida Panhandle. Consultative research data management support from Data Services in the University Libraries played an integral role in the development of the training curriculum. Emphasizing the importance of data quality to the field workers at the beginning of this training curriculum was a vital part of its success. Also critical for success was the research group’s investment of time and effort to work with field workers and improve data management systems. We compare this case study to three others in the literature to compare and contrast data management processes and procedures. This case study serves as one example of how targeted training and efforts in data and project management for a research project can lead to substantial improvements in research data quality.

Published on 2019-09-04 10:02:51

In the case of the African continent, the estimates of most climate forcing components are associated with large uncertainties, above all the greenhouse gas budget. The EU-funded SEACRIFOG project is designing an observation network which aims at reducing these uncertainties. In this practice paper, we present the various steps towards the design of this network and discuss the data-related implications. This includes the formulation of appropriate observational requirements for each variable considered essential to quantify Africa-wide climate forcing as well as an assessment of corresponding available observational infrastructures and data in order to determine data gaps, needs and priorities. The results are intended to inform the design of an interoperable African data infrastructure for environmental observations.

Published on 2019-08-30 09:52:14