Discovering Authoritative Reference Material

2011 ◽  
pp. 137-147
Author(s):  
Lettie Y. Conrad
Keyword(s):  
Reference Material ◽  
Data Management ◽  
Digital Communications ◽  
Information Delivery ◽  
Website Design ◽  
Technological Advancement ◽  
Traditional Methods ◽  
Challenges And Opportunities

For reference publishing, recent revolutions in digital communications undermine the success of traditional methods of information delivery and retrieval. The need to present online reference material for easy discoverability presents challenges and opportunities for technological advancement – for data management and website design. Equally, reference discoverability demands that we foster a greater understanding of what today’s researchers need, and incorporate that knowledge into modern publishing tactics.

The Impact of Emerging Technologies on the Law of Armed Conflict

2019 ◽  
Keyword(s):  
Armed Conflict ◽  
New Technologies ◽  
Emerging Technologies ◽  
Legal Issues ◽  
Technological Advancement ◽  
Law Of Armed Conflict ◽  
Legal Challenges ◽  
Challenges And Opportunities ◽  
The Law ◽  
The Impact

Emerging technologies have always played an important role in armed conflict. From the crossbow to cyber capabilities, technology that could be weaponized to create an advantage over an adversary has inevitably found its way into military arsenals for use in armed conflict. The weaponization of emerging technologies, however, raises challenging legal issues with respect to the law of armed conflict. As States continue to develop and exploit new technologies, how will the law of armed conflict address the use of these technologies on the battlefield? Is existing law sufficient to regulate new technologies, such as cyber capabilities, autonomous weapons systems, and artificial intelligence? Have emerging technologies fundamentally altered the way we should understand concepts such as law-of-war precautions and the principle of distinction? How can we ensure compliance and accountability in light of technological advancement? This book explores these critical questions while highlighting the legal challenges—and opportunities—presented by the use of emerging technologies on the battlefield.

scholarly journals Challenges and Opportunities of E-Procurement in the Construction Industry

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Mansur Hamma-adama ◽  
◽  
Abdul-Basit Sa’eed Ahmad ◽  
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Industrial Revolution ◽  
Qualitative Content Analysis ◽  
Technological Advancement ◽  
Left Behind ◽  
Challenges And Opportunities ◽  
Lack Of Commitment ◽  
Cost Of Construction ◽  
Construction Works

Construction Industry is evolving amid the fourth industrial revolution. Transportation, commerce, manufacturing and many other industries ripened the current technological advancement and are striving to utilise every development in the IT sector. The procurement of construction works is known to be very conventional and backward in the adoption of digitalisation. The construction industry's procurement and supply chain are blamed for the most inflated cost of construction projects, mainly attributed to a lack of transparency and trust between the industry stakeholders. This research explores the challenges of E-procurement adoption in the industry and identifies the potential opportunities for its usage. This investigation's data are acquired through interviews, and the data are analysed using qualitative content analysis. This study reveals compounding challenges (i.e., corruption and lack of commitment) that lead to the failure of such efforts in Nigeria and the potential prospects (i.e., transparency and efficiency). This study is essential in developing a more effective and transparent process of procurement so that the Nigerian construction industry is not be left behind in the fast-digitalising markets.

Data Management Challenges and Opportunities in Cloud Computing

2012 ◽  
pp. 323-323 ◽  
Author(s):  
Kyuseok Shim ◽  
Sang Kyun Cha ◽  
Lei Chen ◽  
Wook-Shin Han ◽  
Divesh Srivastava ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Challenges And Opportunities

Data Management in the Cloud: Challenges and Opportunities

2012 ◽  
Vol 4 (6) ◽  
pp. 1-138 ◽  
Author(s):  
Divyakant Agrawal ◽  
Sudipto Das ◽  
Amr El Abbadi
Keyword(s):  
Data Management ◽  
Challenges And Opportunities

scholarly journals Machine learning for energy-water nexus: challenges and opportunities

2018 ◽  
Vol 2 (3) ◽  
pp. 228-267 ◽  
Author(s):  
Zaidi ◽  
Chandola ◽  
Allen ◽  
Sanyal ◽  
Stewart ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Systems ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Technological Advancement ◽  
Research Directions ◽  
Learning Techniques ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
System Sustainability

Modeling the interactions of water and energy systems is important to the enforcement of infrastructure security and system sustainability. To this end, recent technological advancement has allowed the production of large volumes of data associated with functioning of these sectors. We are beginning to see that statistical and machine learning techniques can help elucidate characteristic patterns across these systems from water availability, transport, and use to energy generation, fuel supply, and customer demand, and in the interdependencies among these systems that can leave these systems vulnerable to cascading impacts from single disruptions. In this paper, we discuss ways in which data and machine learning can be applied to the challenges facing the energy-water nexus along with the potential issues associated with the machine learning techniques themselves. We then survey machine learning techniques that have found application to date in energy-water nexus problems. We conclude by outlining future research directions and opportunities for collaboration among the energy-water nexus and machine learning communities that can lead to mutual synergistic advantage.

Data Management at the University of Iowa: A University Libraries Report on Campus Research Data Needs

2020 ◽  
Author(s):  
Shawn Averkamp ◽  
Xiaomei Gu ◽  
Ben Rogers
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Data Storage ◽  
Analysis Data ◽  
Data Publishing ◽  
Second Phase ◽  
Sensitive Data ◽  
University Of Iowa ◽  
Challenges And Opportunities ◽  
The University

<p>This data management report was commissioned by the University of Iowa Libraries with the intention of performing a survey of the campus landscape and identifying gaps in data management services. The first stage of data collection consisted of a survey conducted during summer 2012 to which 784 responses were received. The second phase of data collection consisted of approximately 40 in-depth interviews with individuals from the campus and were completed during summer 2013. Findings are presented as challenges and opportunities within five broad areas of data management: data management planning, data storage, data organization and analysis, data publishing and dissemination and sensitive data and compliance, with additional findings reported in the areas of research culture and funding models.</p>

Comparison Study of Different NoSQL and Cloud Paradigm for Better Data Storage Technology

2018 ◽  
pp. 312-343
Author(s):  
Pankaj Lathar ◽  
K. G. Srinivasa ◽  
Abhishek Kumar ◽  
Nabeel Siddiqui
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Data Storage ◽  
High Performance ◽  
Large Scale ◽  
Web Based ◽  
Storage Technology ◽  
Data Store ◽  
Challenges And Opportunities ◽  
User Data

Advancements in web-based technology and the proliferation of sensors and mobile devices interacting with the internet have resulted in immense data management requirements. These data management activities include storage, processing, demand of high-performance read-write operations of big data. Large-scale and high-concurrency applications like SNS and search engines have appeared to be facing challenges in using the relational database to store and query dynamic user data. NoSQL and cloud computing has emerged as a paradigm that could meet these requirements. The available diversity of existing NoSQL and cloud computing solutions make it difficult to comprehend the domain and choose an appropriate solution for a specific business task. Therefore, this chapter reviews NoSQL and cloud-system-based solutions with the goal of providing a perspective in the field of data storage technology/algorithms, leveraging guidance to researchers and practitioners to select the best-fit data store, and identifying challenges and opportunities of the paradigm.

Challenges and Opportunities in Big Data Processing

Big Data ◽  
2016 ◽  
pp. 2074-2097 ◽  
Author(s):  
Jaroslav Pokorny ◽  
Bela Stantic
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Management ◽  
File Systems ◽  
Distributed File Systems ◽  
Big Data Processing ◽  
Data Management Systems ◽  
Scalable Systems ◽  
Challenges And Opportunities ◽  
Special Category

The development and extensive use of highly distributed and scalable systems to process Big Data have been widely considered. New data management architectures, e.g. distributed file systems and NoSQL databases, are used in this context. However, features of Big Data like their complexity and data analytics demands indicate that these concepts solve Big Data problems only partially. A development of so called NewSQL databases is highly relevant and even special category of Big Data Management Systems is considered. In this work we will discuss these trends and evaluate some current approaches to Big Data processing, identify the current challenges, and suggest possible research directions.

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