Emerging Approaches to Data Management for a New Geospatial Science Research

2018 ◽  
pp. 304-336
Author(s):  
Joyce Gosata Maphanyane ◽  
Read Brown Mthanganyika Mapeo ◽  
Sethunya Simela
Keyword(s):  
Data Management ◽  
Science Research ◽  
Geospatial Data ◽  
Science Data ◽  
The Subject ◽  
Management Optimization

Chapter 19 and Chapter 20 are on the emerging approaches to data management for a new geospatial science research. This chapter gives the essences and the methodologies of data matter perspective, and it has two sections; Section A highlights the subject theme; the essences of geospatial science data matter; while Section B expands that into the geospatial science data methodologies. Chapter 20 is the about the data management optimization perspective. It has only one section; Section C, that develops further the essence and methodologies of geospatial data cultivated in these two previous sections. The whole analytical discussion is in the emerging fields and how they had optimized and totally changed the geospatial science data management panorama.

scholarly journals Research data management in Turkey: perceptions and practices

2017 ◽  
Vol 35 (2) ◽  
pp. 271-289 ◽  
Author(s):  
Arsev Umur Aydinoglu ◽  
Guleda Dogan ◽  
Zehra Taskin
Keyword(s):  
Data Management ◽  
Online Survey ◽  
Management Practices ◽  
Cost Effective ◽  
Science Research ◽  
Research Data ◽  
Content Type ◽  
Research Data Management ◽  
Data Practices ◽  
The Subject

Purpose The massive increase in research data being produced nowadays has highlighted the importance of research data management (RDM) to science. Research data not only have to be cost effective but also reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the perceptions and practices of Turkish researchers on the subject of RDM. Design/methodology/approach An online survey was distributed to the academicians in 25 universities in Turkey, and 532 responses were gathered. Findings Results indicate that although Turkish researchers are aware of the benefits of data management, are willing to share their research data with certain groups, and have decent preservation habits, they express that they lack the technical skills and knowledge needed for RDM. In addition, no institutionalized support (staff, training, software, and hardware) is provided to researchers. Research limitations/implications A well-structured data strategy or policy that includes resource allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is required for better data management practices among researchers in Turkey. Originality/value This is the first study that investigates the data practices of Turkish academics who produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the growing literature on RDM.

A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure

2010 ◽  
Vol 368 (1925) ◽  
pp. 3859-3873 ◽  
Author(s):  
Guy C. Warner ◽  
Jesse M. Blum ◽  
Simon B. Jones ◽  
Paul S. Lambert ◽  
Kenneth J. Turner ◽  
...  
Keyword(s):  
Social Science ◽  
Data Fusion ◽  
Data Management ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Project Approach ◽  
Computing Power ◽  
Social Science Data ◽  
Using Data

The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analytical methodologies, such as microsimulation, and increases in computing power. These rich resources do, however, bring with them substantial challenges associated with organizing and using data. These processes are often referred to as ‘data management’. The Data Management through e-Social Science (DAMES) project is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data-fusion process that is central to the project approach. It covers: the background and requirements for provision of resources by DAMES; the use of grid technologies to provide easy-to-use tools and user front-ends for several common social science data-management tasks such as data fusion; the approach taken to solve problems related to data resources and metadata relevant to social science applications; and the implementation of the architecture that has been designed to achieve this infrastructure.

Emerging Approaches to Data Management for a New Geospatial Science Research

2018 ◽  
pp. 337-353
Author(s):  
Joyce Gosata Maphanyane ◽  
Read Brown Mthanganyika Mapeo ◽  
Sethunya Simela
Keyword(s):  
Data Management ◽  
Communication Networks ◽  
Data Science ◽  
Technological Development ◽  
Science Research ◽  
Hyperspectral Data ◽  
Software Algorithms ◽  
Quantum Leap ◽  
Management Optimization ◽  
Increase In Accuracy

This chapter is a continuation of themes discussed in Chapter 19. It draws attention to the newly emerging fields and the growth they injected in geospatial science research procedures. It analytically examines the new fields' role in data management optimization perspectives that emanate from the history of their developments and applications. A robust and rigorous data science methodology framework necessary for the success of a geospatial science research has been submitted, its components and challenges thereof are scrutinized. The overall analyses indicate increased growth in the collaborative efforts and a quantum leap in geospatial science technological development. The superior ICT tools: the Internet, communication networks; high performance computer infrastructure and sophisticated software algorithms: Big Data and cloud computing; increase in accuracy for geo-referencing tools: the GPS and other systems like CORS; and lastly increase in availability of geospatial data including the satellite images and hyperspectral data.

scholarly journals IMPLEMENTING THE GROUP ON EARTH OBSERVATIONS DATA MANAGEMENT PRINCIPLES: OBSERVATIONS OF A SCIENTIFIC DATA CENTER

2017 ◽  
Vol XLII-3/W2 ◽  
pp. 51-55
Author(s):  
R. R. Downs
Keyword(s):  
Data Management ◽  
Data Center ◽  
Management Practices ◽  
Earth Science ◽  
Scientific Data ◽  
Geospatial Data ◽  
Data Repository ◽  
Science Data ◽  
Earth Observations ◽  
Earth Science Data

The Group on Earth Observations (GEO) Data Management Principles (DMP) provide direction for managing geospatial data and related information products and services. Offering opportunities for enabling discovery, accessibility, usability, preservation, and curation, the GEO DMP challenge repositories, such as scientific archives and data centers, to improve practices that foster the use of Earth science data today and in the future. In addition, the Data Management Principles Implementation Guidelines (IG) offer many practical suggestions for implementing the DMP with examples that can inform the consideration of options for improving geospatial data management practices. Implementing such improvements offers value to the users of geospatial data by enabling data providers to support the use of the data products and services that they disseminate. Adopting these improvements also can assist repositories in their efforts to meet the requirements for attaining data repository certification, which offers value for repositories and their stakeholders. This article shows how repositories can improve data management practices for geospatial data by adopting the GEO DMP, with examples drawn from a scientific data center. Current and future opportunities for improving data management practices to attain data repository certification also are described along with practical approaches that repositories can adopt in the short term.

Heuristische Textpraktiken in den Wissenschaften

2020 ◽  
Vol 48 (1) ◽  
pp. 1-46
Author(s):  
Michael Bender ◽  
Marcus Müller
Keyword(s):  
Science Research ◽  
Annotation Scheme ◽  
Scientific Debate ◽  
Domain Specific ◽  
Current State ◽  
Scientific Disciplines ◽  
Textual Practices ◽  
Collaborative Annotation ◽  
The Subject ◽  
State Of Research

AbstractThis article contains a comparative study of heuristic textual practices in various scientific disciplines. By this we mean formulation practices with which new knowledge is generated in institutionally influenced routines and connected to existing knowledge, e. g. ‚highlighting the relevance of a research topic‘, ‚defining a concept‘ or ‚supporting a statement argumentatively‘.The aim is to find out to what extent such textual practices occur in different scientific disciplines, how they are distributed and combined. Furthermore, we study the effects domain-specific contexts have on heuristic textual practices. The data basis of our study is a corpus of 65 dissertations from the 13 different faculties of the TU Darmstadt. In the pilot study we report here, we examined the introductory chapters of the dissertations. Methodologically, it is an annotation study: Based on the current state of research on the subject, we have derived a basic annotation scheme, which we have developed and refined in a collaborative process of guideline creation. Our study affiliates on socio-pragmatic research on text production and formulation routines in the sciences. It is theoretically informed by the philosophy of science research on heuristics, methodically we make a contribution to the scientific debate on collaborative annotation procedures.

scholarly journals Uncomfortable Decisions

2022 ◽  
Author(s):  
Paul Bloom ◽  
Laurie Paul
Keyword(s):  
Decision Making ◽  
Social Science ◽  
Career Change ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Decision Making Processes ◽  
Social Science Data ◽  
Personal Decision ◽  
Algorithmic Process

Some decision-making processes are uncomfortable. Many of us do not like to make significant decisions, such as whether to have a child, solely based on social science research. We do not like to choose randomly, even in cases where flipping a coin is plainly the wisest choice. We are often reluctant to defer to another person, even if we believe that the other person is wiser, and have similar reservations about appealing to powerful algorithms. And, while we are comfortable with considering and weighing different options, there is something strange about deciding solely on a purely algorithmic process, even one that takes place in our own heads.What is the source of our discomfort? We do not present a decisive theory here—and, indeed, the authors have clashing views over some of these issues—but we lay out the arguments for two (consistent) explanations. The first is that such impersonal decision-making processes are felt to be a threat to our autonomy. In all of the examples above, it is not you who is making the decision, it is someone or something else. This is to be contrasted with personal decision-making, where, to put it colloquially, you “own” your decision, though of course you may be informed by social science data, recommendations of others, and so on. A second possibility is that such impersonal decision-making processes are not seen as authentic, where authentic decision making is one in which you intentionally and knowledgably choose an option in a way that is “true to yourself.” Such decision making can be particularly important in contexts where one is making a life-changing decision of great import, such as the choice to emigrate, start a family, or embark on a major career change.

scholarly journals TrIAS, leveraging citizen science data to monitor invasive species in Belgium

2018 ◽  
Vol 2 ◽  
pp. e24749
Author(s):  
Quentin Groom ◽  
Tim Adriaens ◽  
Damiano Oldoni ◽  
Lien Reyserhove ◽  
Diederik Strubbe ◽  
...  
Keyword(s):  
Invasive Species ◽  
Alien Species ◽  
Citizen Science ◽  
Invasive Alien Species ◽  
Science Research ◽  
Open Science ◽  
Policy Support ◽  
Science Data ◽  
Common View ◽  
Indispensable Tool

Reducing the damage caused by invasive species requires a community approach informed by rapidly mobilized data. Even if local stakeholders work together, invasive species do not respect borders, and national, continental and global policies are required. Yet, in general, data on invasive species are slow to be mobilized, often of insufficient quality for their intended application and distributed among many stakeholders and their organizations, including scientists, land managers, and citizen scientists. The Belgian situation is typical. We struggle with the fragmentation of data sources and restrictions to data mobility. Nevertheless, there is a common view that the issue of invasive alien species needs to be addressed. In 2017 we launched the Tracking Invasive Alien Species (TrIAS) project, which envisages a future where alien species data are rapidly mobilized, the spread of exotic species is regularly monitored, and potential impacts and risks are rapidly evaluated in support of policy decisions (Vanderhoeven et al. 2017). TrIAS is building a seamless, data-driven workflow, from raw data to policy support documentation. TrIAS brings together 21 different stakeholder organizations that covering all organisms in the terrestrial, freshwater and marine environments. These organizations also include those involved in citizen science, research and wildlife management. TrIAS is an Open Science project and all the software, data and documentation are being shared openly (Groom et al. 2018). This means that the workflow can be reused as a whole or in part, either after the project or in different countries. We hope to prove that rapid data workflows are not only an indispensable tool in the control of invasive species, but also for integrating and motivating the citizens and organizations involved.

scholarly journals Exploring, modelling, and simulating the Feeling of Comfort in residential settings

2021 ◽  
Author(s):  
◽  
German Molina
Keyword(s):  
New Zealand ◽  
Science Research ◽  
Personal Factors ◽  
Building Science ◽  
Holistic View ◽  
Research And Practice ◽  
Making Sense ◽  
The People ◽  
The Subject ◽  
The Mind

<p><b>The fact that comfort is a subjective state of the mind is widely accepted by engineers, architects and building scientists. Despite this, capturing all the complexity, subjectivity and richness of this construct in models that are useful in building science contexts is far from straightforward. By prioritizing usability, building science has produced models of comfort (e.g., acoustic, visual and thermal) that overly simplify this concept to something nearly objective that can be directly associated with people’s physiology and measurable and quantifiable environmental factors. This is a contradiction because, even if comfort is supposed to be subjective, most of the complexity of “the subject” is avoided by focusing on physiology; and, even if comfort is supposed to reside in the mind, the cognitive processes that characterize the mind are disregarded. This research partially mitigates this contradiction by exploring people’s non-physical personal factors and cognition within the context of their comfort and by proposing a way in which they can be incorporated into building science research and practice. This research refers to these elements together—i.e., people’s non-physical personal factors and cognition—as “the mind”.</b></p> <p>This research proposes a new qualitative model of the Feeling of Comfort that embraces “the mind”. This model was developed from the results of a first study in which 18 people—from Chile and New Zealand—were asked to describe “a home with good daylight” and “a warm home” in their own words. These results were then replicated in a second study in which another group of 24 people—also from Chile and New Zealand—described “a home with good acoustic performance”, “a home with good air quality” and “a pleasantly cool home”. The Feeling of Comfort model not only was capable of making sense of the new data (gathered in this second study) but also proved to be simple enough to be useful in the context of comfort research and practice. For instance, it guided the development of a quantitative Feeling of Comfort model and also of a prototype building simulation tool that embraces “the mind” and thus can potentially estimate people’s Feeling of Comfort.</p> <p>This research concludes that embracing “the mind” is not only possible but necessary. The reason for this is that “the mind” plays a significant role in the development of people’s comfort. Thus, theories and models of comfort that ignore it fail to represent properly the concept of comfort held by the people for whom buildings are designed. However, incorporating “the mind” into building science’s research and practice implies embracing tools, research methods and conceptual frameworks that have historically not been used by such a discipline. Specifically, it concludes that building science should normalize a more holistic view of comfort and perform more exploratory and qualitative research.</p>

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