Improving Government Decision Making in Africa through Digital Data Collection

2020 ◽  
Author(s):  
Johan Breytenbach ◽  
Mahier Hattas
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Digital Data ◽  
Government Decision

Using digital data collection tools to improve overall cost-efficiency and provide timely analysis for decision making during invasive species eradication campaigns

2014 ◽  
Vol 41 (6) ◽  
pp. 499 ◽  
Author(s):  
David J. Will ◽  
Karl J. Campbell ◽  
Nick D. Holmes
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Cost Efficiency ◽  
Relational Databases ◽  
Cost Effective ◽  
Digital Data ◽  
Capital Costs ◽  
Project Costs ◽  
Time Required ◽  
Data Collection Effort

Context Worldwide, invasive vertebrate eradication campaigns are increasing in scale and complexity, requiring improved decision making tools to achieve and validate success. For managers of these campaigns, gaining access to timely summaries of field data can increase cost-efficiency and the likelihood of success, particularly for successive control-event style eradications. Conventional data collection techniques can be time intensive and burdensome to process. Recent advances in digital tools can reduce the time required to collect and process field information. Through timely analysis, efficiently collected data can inform decision making for managers both tactically, such as where to prioritise search effort, and strategically, such as when to transition from the eradication phase to confirmation monitoring. Aims We highlighted the advantages of using digital data collection tools, particularly the potential for reduced project costs through a decrease in effort and the ability to increase eradication efficiency by enabling explicit data-informed decision making. Methods We designed and utilised digital data collection tools, relational databases and a suite of analyses during two different eradication campaigns to inform management decisions: a feral cat eradication utilising trapping, and a rodent eradication using bait stations. Key results By using digital data collection during a 2-year long cat eradication, we experienced an 89% reduction in data collection effort and an estimated USD42 845 reduction in total costs compared with conventional paper methods. During a 2-month rodent bait station eradication, we experienced an 84% reduction in data collection effort and an estimated USD4525 increase in total costs. Conclusions Despite high initial capital costs, digital data collection systems provide increasing economics as the duration and scale of the campaign increases. Initial investments can be recouped by reusing equipment and software on subsequent projects, making digital data collection more cost-effective for programs contemplating multiple eradications. Implications With proper pre-planning, digital data collection systems can be integrated with quantitative models that generate timely forecasts of the effort required to remove all target animals and estimate the probability that eradication has been achieved to a desired level of confidence, thus improving decision making power and further reducing total project costs.

scholarly journals Incident Command Futurism

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Josh Gravenmier ◽  
Greg McGowan
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Mechanical Response ◽  
Cost Savings ◽  
Risk Identification ◽  
Digital Data ◽  
Digital Information ◽  
Incident Command ◽  
Response Status ◽  
Unified Command

ABSTRACT The availability of integrated remote sensing platforms and digital data collection and sharing tools is changing spill response. These tools facilitate a more effective and rapid decision-making process that can increase resource protection, improve responder safety, and reduce response costs. Early detection and response are a key to preventing smaller incidents from becoming larger. A variety of innovative tools now exist or are in development that could assist facilities and responders in the early stages and throughout an incident event to reduce human, environmental, and economic impacts. Real time field data collection for key parameters such as oil thickness and trajectory, SCAT data, oiled wildlife details, and resources at risk identification, allows for more robust data to be shared rapidly throughout the response operation. This information facilitates more effectively targeted deployment and re-deployment of human and mechanical response assets, and more immediate assessment of both environmental impacts and cleanup progress. Auto-population of incident command system forms as well as better document sharing and document retention through remote and cloud-based file saving platforms can improve the administrative and functional aspects of the response, contributing to enhanced efficiency. The ability to identify and effectively respond to rapidly changing circumstances provides the Unified Command with new tools to make better decisions and keep the public informed of progress. This paper considers new and emerging technologies as they may be applied to the work in a unified command setting, and how they may allow us to compress the operational period for decision-making and action, more accurately and more rapidly understand and share the spill response status, and how we may be able to enhance responder safety and recognize cost savings. We also consider some inherent risks associated with reliance on integrated technologies and digital information and will offer suggestions for drills and exercises to test and optimize these tools.

A SYSTEM FOR INTEGRATED SCAT DATA COLLECTION AND MANAGEMENT: ESCAT, SCATDB, AND PHOTOLOGGER

2008 ◽  
Vol 2008 (1) ◽  
pp. 481-484 ◽  
Author(s):  
Jeffrey F. Lankford ◽  
Ian Zelo ◽  
Matt R. Stumbaugh
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Field Data ◽  
Digital Data ◽  
Handheld Devices ◽  
Handheld Computing ◽  
Field Data Collection ◽  
Digital Options ◽  
Multiple Field ◽  
Collection And Management

ABSTRACT During response, oiled shorelines must be surveyed to guide cleanup operations. The Shoreline Cleanup and Assessment Technique (SCAT) is a standard method for conducting these surveys. Multiple field teams often conduct SCAT. SCAT surveys quickly produce a large and complex dataset comprised of SCAT observations, GPS positions, and photographs. In order to guide response decision-making, SCAT field data must be processed and analyzed in a timely manner. Until recently, SCAT and GPS data were collected on standardized paper worksheets, transcribed to electronic form, and then incorporated into maps and other decision-making products. Photographs were not tightly managed alongside SCAT data. Today, with the emergence of robust handheld computing technology, the deficiencies inherent in paper data collection are no longer necessary or acceptable. Paper data collection can be slow, error prone, and lacking quality control and integration with GPS technology. Digital options are available to address these challenges. To improve methods, the Office of Response and Restoration is developing a digital field data collection and management system for SCAT data and photographs composed of: (1) specialized software for efficient SCAT data collection with GPS enabled handheld devices, (2) a relational SCAT database which expedites the synthesis of field data into decision making products, promotes community standards, and supports standard paper worksheet and digital data collection methods, and (3) an image database which allows for the processing, documenting, and sharing of large quantities of digital photographs. For this project, commonly used, readily available, and Open Source computing resources were chosen so that end-users could easily test, adopt, and improve this system.

Data Collection

1994 ◽  
Vol 3 (3) ◽  
pp. 55-66 ◽  
Author(s):  
Lesley B. Olswang ◽  
Barbara Bain
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Treatment Efficacy ◽  
Qualitative Information ◽  
Treatment Progress ◽  
Clinical Process ◽  
Birthday Party ◽  
Speech Language Pathologist ◽  
Intuitive Decision Making ◽  
Decision Making Model

For many of us, not having data concerning a client’s progress during treatment is tantamount to being unprepared for a lecture, or showing up at a birthday party without a present—totally unthinkable. This zealous position is based on the assumption that clinical decisions regarding treatment efficacy should be based on data. Data, in this case, refers to both quantitative and qualitative information that provides evidence for deciding the course of treatment. This is not to say that data can and should be collected on every aspect of the clinical process. Indeed, intuitive decision-making on the part of the speech-language pathologist is often warranted. But in general, a series of decisions regarding whether or not treatment is working, can and should be based on data. This article examines the ways in which we can measure treatment progress, and provides guidelines for the reader in the use of a data-based, decision-making model.

Cultivating Trustworthy Artificial Intelligence in Digital Government

2020 ◽  
pp. 089443932098012
Author(s):  
Teresa M. Harrison ◽  
Luis Felipe Luna-Reyes
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Policy Analysis ◽  
Public Trust ◽  
Governance Structures ◽  
Cognitive Tools ◽  
Lens Model ◽  
Digital Government ◽  
Government Decision ◽  
Decision Making Processes

While there is growing consensus that the analytical and cognitive tools of artificial intelligence (AI) have the potential to transform government in positive ways, it is also clear that AI challenges traditional government decision-making processes and threatens the democratic values within which they are framed. These conditions argue for conservative approaches to AI that focus on cultivating and sustaining public trust. We use the extended Brunswik lens model as a framework to illustrate the distinctions between policy analysis and decision making as we have traditionally understood and practiced them and how they are evolving in the current AI context along with the challenges this poses for the use of trustworthy AI. We offer a set of recommendations for practices, processes, and governance structures in government to provide for trust in AI and suggest lines of research that support them.

LATAR BELAKANG PENGAMBILAN KEPUTUSAN VLADIMIR PUTIN ATAS ISU KRIMEA

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Osvaldo Victor Alfonso ◽  
Agung Yudhistira Nugroho
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Identity Politics ◽  
Research Method ◽  
Qualitative Method ◽  
Military Intervention ◽  
Electronic Media ◽  
Economic Politics ◽  
Rational Choices ◽  
Vladimir Putin

AbstrakPenelitian ini menggambarkan tentang berbagai latar belakang pengambilan keputusan Putin atas isu Krimea yang melihat dasar-dasar pengambilan keputusan seperti intuisi, pengalaman, fakta, wewenang, dan rasionalitas yang memengaruhi Putin dalam melakukan aksi aneksasi Krimea tersebut. Dalam penulisan skripsi ini, sang penulis menggunakan kerangka teori Pengambilan Keputusan (Decision Making) yang merupakan topik utama sekaligus pisau analisa dalam penelitian ini. Metode penelitian yang digunakan oleh sang penulis dalam penyusunan skripsi ini adalah metode kualitatif. Adapun teknik pengumpulan data yang digunakan oleh sang penulis dalam memperoleh data adalah melalui wawancara dan studi pustaka yang menelaah sejumlah buku, jurnal, artikel ilmiah, dan media elektronik. Hasil penelitian menunjukkan bahwa latar belakang pengambilan keputusan Vladimir Putin adalah berdasarkan pilihan rasional dengan melihat pertimbangan materil seperti memberi keuntungan di sektor keamanan, ekonomi, politik, memberikan peluang Rusia menjadi negara adidaya, dan pengamanan jalur pipa gas Rusia di Ukraina dan Krimea. Yang menarik dari tindakan yang diinisiasi oleh Putin itu adalah aksi tersebut dalam merebut suatu wilayah tanpa pencurahan darah. Ini adalah hal yang menarik bagi sang penulis karena bagaimana mungkin suatu intervensi militer di suatu wilayah tidak terjadi penyerangan dari pihak luar ke dalam suatu wilayah, dalam hal ini adalah aksi Rusia kepada Krimea. Politik keamanan, politik identitas, dan politik ekonomi mewarnai Putin dalam pengambilan keputusannya atas isu Krimea tersebut.Kata Kunci: Vladimir Putin, Pengambilan Keputusan, Pilihan                          Rasional, Rusia, Krimea, Ukraina.Abstract This research describes the various backgrounds of Putin's decision making on the Crimean issue which looks at the basics of decision making such as intuition, experience, facts, authority and rationality that influenced Putin in carrying out the Crimean annexation. In writing this thesis, the writer uses the theoretical framework of Decision Making which is the main topic as well as the analysis knife in this research. The research method used by the author in the preparation of this thesis is a qualitative method. The data collection techniques used by the author in obtaining data are through interviews and literature studies that examine a number of books, journals, scientific articles, and electronic media. The results show that the background of Vladimir Putin's decision making is based on rational choices by looking at material considerations such as providing benefits in the security, economic, political sectors, giving Russia the opportunity to become a superpower, and securing Russian gas pipelines in Ukraine and Crimea. What's interesting about the action initiated by Putin is that it seizes an area without shedding blood. This is an interesting matter for the author because how could a military intervention in a region not occur from outside attacks into an area, in this case Russia's action against Crimea. Security politics, identity politics and economic politics colored Putin in his decision making on the Crimean issue. Keywords:  Vladimir Putin, Decision Making, Rational Choice,                          Rusia, Crimea, Ukraine.

Sign in / Sign up

Export Citation Format

Share Document