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| data analysis real estate: Private Real Estate Investment Roger J. Brown, 2005-03-29 Fiduciary responsibilities and related court-imposed liabilities have forced investors to assess market conditions beyond gut level, resulting in the development of sophisticated decision-making tools. Roger Brown's use of historical real estate data enables him to develop tools for gauging the impact of circumstances on relative risk. His application of higher level statistical modeling to various aspects of real estate makes this book an essential partner in real estate research. Offering tools to enhance decision-making for consumers and researchers in market economies of any country interested in land use and real estate investment, his book will improve real estate market efficiency. With property the world's biggest asset class, timely data on housing prices just got easier to find and use. - Excellent mixture of theory and application - Data and database analysis techniques are the first of their kind |
| data analysis real estate: Real Estate Analysis in the Information Age Kimberly Winson-Geideman, Andy Krause, Clifford A. Lipscomb, Nick Evangelopoulos, 2017-11-09 The creation, accumulation, and use of copious amounts of data are driving rapid change across a wide variety of industries and academic disciplines. This ‘Big Data’ phenomenon is the result of recent developments in computational technology and improved data gathering techniques that have led to substantial innovation in the collection, storage, management, and analysis of data. Real Estate Analysis in the Information Age: Techniques for Big Data and Statistical Modeling focuses on the real estate discipline, guiding researchers and practitioners alike on the use of data-centric methods and analysis from applied and theoretical perspectives. In it, the authors detail the integration of Big Data into conventional real estate research and analysis. The book is process-oriented, not only describing Big Data and associated methods, but also showing the reader how to use these methods through case studies supported by supplemental online material. The running theme is the construction of efficient, transparent, and reproducible research through the systematic organization and application of data, both traditional and 'big'. The final chapters investigate legal issues, particularly related to those data that are publicly available, and conclude by speculating on the future of Big Data in real estate. |
| data analysis real estate: Market Analysis for Real Estate Rena Mourouzi-Sivitanidou, 2020-08-06 Market Analysis for Real Estate is a comprehensive introduction to how real estate markets work and the analytical tools and techniques that can be used to identify and interpret market signals. The markets for space and varied property assets, including residential, office, retail, and industrial, are presented, analyzed, and integrated into a complete understanding of the role of real estate markets within the workings of contemporary urban economies. Unlike other books on market analysis, the economic and financial theory in this book is rigorous and well integrated with the specifics of the real estate market. Furthermore, it is thoroughly explained as it assumes no previous coursework in economics or finance on the part of the reader. The theoretical discussion is backed up with numerous real estate case study examples and problems, which are presented throughout the text to assist both student and teacher. Including discussion questions, exercises, several web links, and online slides, this textbook is suitable for use on a variety of degree programs in real estate, finance, business, planning, and economics at undergraduate and MSc/MBA level. It is also a useful primer for professionals in these disciplines. |
| data analysis real estate: Real Estate Market Valuation and Analysis Joshua Kahr, Michael C. Thomsett, 2006-02-10 A fresh, insightful look at how real estate professionals actually value properties and analyze markets. The focus on different product types as well as market segments are especially useful. --Barry Hersh, AICP, Associate Professor of Real Estate and Urban Planning, City University of New York This in-depth look at the core tools of real estate valuation will show you how to analyze the real estate market and assess the financial feasibility of a project. Many people go with their instincts or past experience when reviewing the financials and fail to utilize the useful data and analytical tools available in this field. Get the analytical data and tools you need to assess the financial feasibility of any project. Order your copy today. |
| data analysis real estate: Private Real Estate Investment Roger J. Brown, 2005-02-03 Fiduciary responsibilities and related court-imposed liabilities have forced investors to assess market conditions beyond gut level, resulting in the development of sophisticated decision-making tools. Roger Brown's use of historical real estate data enables him to develop tools for gauging the impact of circumstances on relative risk. His application of higher level statistical modeling to various aspects of real estate makes this book an essential partner in real estate research. Offering tools to enhance decision-making for consumers and researchers in market economies of any country interested in land use and real estate investment, his book will improve real estate market efficiency. With property the world's biggest asset class, timely data on housing prices just got easier to find and use. Excellent mixture of theory and application Data and database analysis techniques are the first of their kind |
| data analysis real estate: Applied Quantitative Analysis for Real Estate Sotiris Tsolacos, Mark Andrew, 2020-09-23 To fully function in today’s global real estate industry, students and professionals increasingly need to understand how to implement essential and cutting-edge quantitative techniques. This book presents an easy-to-read guide to applying quantitative analysis in real estate aimed at non-cognate undergraduate and masters students, and meets the requirements of modern professional practice. Through case studies and examples illustrating applications using data sourced from dedicated real estate information providers and major firms in the industry, the book provides an introduction to the foundations underlying statistical data analysis, common data manipulations and understanding descriptive statistics, before gradually building up to more advanced quantitative analysis, modelling and forecasting of real estate markets. Our examples and case studies within the chapters have been specifically compiled for this book and explicitly designed to help the reader acquire a better understanding of the quantitative methods addressed in each chapter. Our objective is to equip readers with the skills needed to confidently carry out their own quantitative analysis and be able to interpret empirical results from academic work and practitioner studies in the field of real estate and in other asset classes. Both undergraduate and masters level students, as well as real estate analysts in the professions, will find this book to be essential reading. |
| data analysis real estate: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| data analysis real estate: Business Geography and New Real Estate Market Analysis Grant Ian Thrall, 2002-04-18 This work focuses on integrating land-use location science with the technology of geographic information systems (GIS). The text describes the basic principles of location decision and the means for applying them in order to improve the real estate decision. |
| data analysis real estate: Real Estate Investing Benedetto Manganelli, 2014-07-21 This book describes in full the major approaches used to evaluate investment in real estate and shows how theory informs decision-aid methods and tools to support such evaluation. The inclusion of numerous examples makes it also a practical guide to assessing the suitability of an investment property. The first part of the text is devoted to an analysis of the housing market through the study of micro- and macroeconomic variables influencing supply and demand, with illustration of how these two components of the market interact. Special attention is given to market research and other preparatory activities able to influence the outcome of the investment. In fact, the quality of the parameters used for the evaluation depends on these activities. The final chapters describe the valuation techniques and highlight their essential features, limitations and potential in relation to ability to manage the investment risk. The book is aimed at graduates who wish to deepen their study of the real estate market and of the methods used to support investment decisions in real estate but also at professionals and managers of companies operating in the real estate market. |
| data analysis real estate: Questions and Answers to Help You Pass the Real Estate Appraisal Exams Jeffrey D. Fisher, Dennis S. Tosh, 2004 Newly updated, Mastering Real Estate Principles, 4th Edition is more organized, more appealing, and more user- friendly than ever before. Known for its workbook format and interactive approach to learning, this new edition features updated content, an enhanced interior design, and a new construction section. This complete learning system comes loaded with multiple teaching tools and instructor resource guide to reduce instructor workload. |
| data analysis real estate: Real Estate Market Research and Analysis Chris Leishman, 2003-04-24 This work is aimed at both students and practitioners in the commercial property and real-estate sector. It sets out the means and methods by which a commercial property rent model should be constructed and estimated, and provides a helpful guide to good property market research practice. |
| data analysis real estate: Real Estate Market Analysis Deborah L. Brett, Adrienne Schmitz, 2015 First ed. entered under Adrienne Schmitz |
| data analysis real estate: Applied Quantitative Analysis for Real Estate Sotiris Tsolacos, Mark Andrew, 2020-09-13 To fully function in today’s global real estate industry, students and professionals increasingly need to understand how to implement essential and cutting-edge quantitative techniques. This book presents an easy-to-read guide to applying quantitative analysis in real estate aimed at non-cognate undergraduate and masters students, and meets the requirements of modern professional practice. Through case studies and examples illustrating applications using data sourced from dedicated real estate information providers and major firms in the industry, the book provides an introduction to the foundations underlying statistical data analysis, common data manipulations and understanding descriptive statistics, before gradually building up to more advanced quantitative analysis, modelling and forecasting of real estate markets. Our examples and case studies within the chapters have been specifically compiled for this book and explicitly designed to help the reader acquire a better understanding of the quantitative methods addressed in each chapter. Our objective is to equip readers with the skills needed to confidently carry out their own quantitative analysis and be able to interpret empirical results from academic work and practitioner studies in the field of real estate and in other asset classes. Both undergraduate and masters level students, as well as real estate analysts in the professions, will find this book to be essential reading. |
| data analysis real estate: Real Estate Modelling and Forecasting Chris Brooks, Sotiris Tsolacos, 2010-04-15 As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners. |
| data analysis real estate: Commercial Real Estate David Geltner, Norman G. Miller, Dr. Jim Clayton, Piet Eichholtz, 2014 Rev. ed. of: Commercial real estate analysis and investments / David M. Geltner ... [et al.]. Mason, Ohio: Thompson South-Western, c2007. |
| data analysis real estate: Market Analysis for Real Estate Stephen F. Fanning, 2005 |
| data analysis real estate: Practical Applications in Appraisal Valuation Modeling M. Steven Kane, Mark R. Linne, Jeffrey A. Johnson, 2004 |
| data analysis real estate: U.S. Housing Market Conditions , 1997 |
| data analysis real estate: Real Estate Analysis Julian Diaz Iii, J. Andrew Hansz, 2010-07-06 Real estate is everywhere. It is where we live, where we play, where we shop, where we work, where we learn. |
| data analysis real estate: What Every Real Estate Investor Needs to Know About Cash Flow... And 36 Other Key Financial Measures, Updated Edition Frank Gallinelli, 2015-11-20 The Classic Guide to Real Estate Investing—Updated for a Re-energized Industry! Real estate is once again a great investment, and this bestselling guide provides everything you need to know to get in now and make your fortune. What Every Real Estate Investor Needs to Know About Cash Flow removes the guesswork from investing in real estate by teaching you how to crunch numbers like a pro, so you can confidently judge a property’s value and ensure it provides long-term returns. Real estate expert, Frank Gallinelli has added new, detailed investment case studies, while maintaining the essentials that have made his book a staple among serious investors. Learn how to measure critical aspects of real estate investments, including: Discounted Cash Flow Net Present Value Capitalization Rate Cash-on-Cash Return Net Operating Income Internal Rate of Return Profitability Index Return on Equity Whether you’re just beginning in real estate investing or you’re a seasoned professional, What Every Real Estate Investor Needs to Know About Cash Flow has what you need to make sure you take the smartest approach for your next investment using proven calculations. |
| data analysis real estate: The Future of Real Estate Home Pricing Anton Roeger IV, 2020-03-03 Today's real estate agent is in the middle of an epic battle. Giant CMA and AVM companies have introduced fancy tech tools that encourage home buyers and sellers to go it alone, without an agent. Your livelihood is on the line. Current home valuation is subjective, unreliable, outdated or just plain wrong. How can you win your clients' trust when they are confused about the best price to list their home? In The Future of Real Estate Home Pricing, Anton Roeger, founder of APC Data Analytics, shows you how innovative new tools, processes and data can help you gain your clients' trust and become a sought-after authority on home buying and selling trends in your area. In this book, you'll learn how to: - build credibility with your clients through accurate, powerful, current and comprehensible property valuation - combat online pricing giants that are misleading your clients with unreliable automatic valuation models (AVMs) - automate your Comparative Market Analysis (CMA) with a new set of accurate, powerful, real-time tools A perfect book for real estate agents and brokers as well as real estate lawyers and investors. |
| data analysis real estate: Real Estate Finance and Investments Peter Linneman, 2020-02 |
| data analysis real estate: Real Estate Appraisal Joseph F. Schram, 2006 Rev. ed. of: Real estate appraisal. c2005. |
| data analysis real estate: Modern Classification and Data Analysis Krzysztof Jajuga, Grażyna Dehnel, Marek Walesiak, 2022-10-16 This volume presents a selection of peer-reviewed papers that address the latest developments in the methodology and applications of data analysis and classification tools to micro- and macroeconomic problems. The contributions were originally presented at the 30th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2021, held online in Poznań, Poland, September 8–10, 2021. Providing a balance between methodological and empirical studies, and covering a wide range of topics, the book is divided into five parts focusing on methods and applications in finance, economics, social issues and to COVID-19 data. The book is aimed at a wide audience, including researchers at universities and research institutions, PhD students, as well as practitioners, data scientists and employees in public statistical institutions. |
| data analysis real estate: Private Real Estate Investment Roger J. Brown, 2012-01-05 A rigorous treatment of the process of private real estate investment from selection to disposition. Techniques combine the author's 40 years of field experience with sound theoretical and empirical academics |
| data analysis real estate: The Geopolitics of Real Estate Dallas Rogers, 2016-10-04 Individual foreign investment in Western nation states is a long-standing geopolitical issue. The expansion of the middle class in BRICS and Asian countries, and their increased activity in Western real estate markets as foreign investors, have introduced new and revived existing cultural and geopolitical sensitivities. In this book, Dallas Rogers develops a new history of foreign real estate investment by mapping the movement of human and financial capital over more than four centuries. The book argues the reconfiguration of Asian geopolitical power has ruptured the conceptual landscape for understanding international land and real estate relations. Drawing on assemblage theories (Latour, Deleuze and Guattari), assemblage analytical tactics (Sassen and Ong) and discursive media theories (Kittler and Foucault) a series of vignettes of land and real estate crisis are presented. The book demonstrates how foreign land claimers and global real estate professionals colonise, subvert and act beyond the governance structures of settler-societies to facilitate new types of capital circulation and accumulation around the world. |
| data analysis real estate: Recent Advancements in Computational Finance and Business Analytics Rangan Gupta, |
| data analysis real estate: Money Laundering in the Real Estate Sector Brigitte Unger, Joras Ferwerda, 2011 In many countries, the real estate sector is vulnerable to money laundering due to a high number of factors including; the high value of assets, price fluctuations and speculation within the market, difficulties in assessing the true value of a house, and the fact that the legal owner is not necessarily the economic owner. In this book, the authors identify a total of 25 characteristics which render a property susceptible to money laundering. The more such characteristics a property exhibits, the more suspicious it becomes. The authors also discover that some of these characteristics weigh heavier than others. Combining economic, econometric and criminological analysis, this multidisciplinary approach shows how to detect criminal investment in the real estate sector. This well-researched book will appeal to government authorities responsible for combating money laundering, international organizations such as the IMF, the UN, the Worldbank and the EU, as well as financial intelligence units in all countries. Real estate associations, real estate research centers, criminologists and economists will also find this book invaluable. |
| data analysis real estate: ICBBEM 2023 Liu Lin, Zhang Kun, Kannimuthu S., 2023-07-24 The 2nd International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2023) was successfully held on 19-21 May 2023 in Hangzhou, China. The conference aims to present the latest research results in the areas related to Big Data, Blockchain and Economic Management, and provide an opportunity for experts and scholars from various fields to meet face-to-face, exchange new ideas and practical experiences, establish business or research relationships, and seek future international cooperation. This volume contains a collection of excellent papers from the conference, presented on topics such as computer software and computer applications, blockchain in data management, e-commerce and digital commerce, and linear regression analysis. We hope that these papers will serve as a reference for young scholars in their future research. |
| data analysis real estate: PropTech and Real Estate Innovations Olayiwola Oladiran, Louisa Dickins, 2024-08-22 This textbook serves as a guide to real estate students and educators on the various property innovations and digital technologies that continue to shape the property industry. The advancement of PropTech in the last few decades has led to significant changes in real estate systems, operations, and practice, and this new textbook provides insight on the past, present, and future of PropTech innovations that have spread across the value chain of real estate through planning, development, management, finance, investment, operations, and transactions. The textbook approaches this subject from the real estate components, asset classes, and submarkets and links them to the associated innovations and digital technologies. It concludes by reviewing the role of education, innovation, skill development, and professionalism as major elements of the future of real estate operations and practice. This book’s unique contributions are in putting the “property” element at the forefront and then illustrating how technology can enhance the various areas of real estate; the focus on how the different innovations and technologies can enhance the economic, environmental, social, and physical efficiency of real estate; and its coverage of some non‐technological innovations like flexible working and more practical areas of real estate innovation such as skills, employability, creativity, and education. It contains 21 case studies and 29 case summaries, which can serve as practice exercises for students. This book will be useful to students in helping them build a knowledge base and understanding of innovation and digital technologies in the industry. Real estate educators can use the textbook as a guide to incorporate real estate innovation and digital technologies into their current teaching and also to develop their real estate curricula through PropTech‐related modules and courses where necessary. It will also be valuable to real estate researchers in search of the theoretical and conceptual linkages, as well as industry practitioners who seek insight into the current and future potential of digital technologies and their applications to real estate operations and practice. |
| data analysis real estate: Economic Analysis of the Digital Economy Avi Goldfarb, Shane M. Greenstein, Catherine Tucker, 2015-05-08 There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. Economics of Digitization identifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop. Economics of Digitization will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research. |
| data analysis real estate: Real Estate Analysis David Rees, 2023-10-09 Real Estate Analysis: A Toolkit for Property Analysts presents economic and financial models, applications and insights, packaged as a toolkit for analysts and other participants in commercial and residential real estate markets. Participants in property markets – analysts, brokers, commentators as well as investors and tenants – move seamlessly across a range of physical and financial markets. They employ models that illuminate market activity: the tools of supply and demand to explain rental trends and to forecast vacancy rates and construction cycles; forecasts of macro-economists foreshadow shoppers’ spending behaviour in shopping malls and the growth in demand for office space; capital market arithmetic to apply discount and capitalisation rates. Currently these topics are often scattered through textbooks. This book brings these tools together and situates them in a real estate market context. Topics addressed include: • The interaction of markets – capital, space and physical assets • Debt, the cost of capital and investment hurdle rates • Real options – valuing lease contracts and land • Risk – what counts, what doesn’t (systemic and non-systemic risk) • Discounted rates and capitalisation rates – interpreting spreads to sovereign bond yields • Externalities – why do markets “fail”; what are the “solutions”? • Property rights – different rules, different outcomes • Exploitation for natural resources (exhaustible, renewable) – how does discounted cash flow analysis (DCF) fit in? • Cost-benefit analysis – the analytics of compensation payments • Forecasting – purpose and process The foundations and the scaffolding that underpin and support real estate market analysis are the focus of this book. Its purpose is to complement, sometimes augment, the subject matter of real estate training programs. The prospective audience includes curious professionals and researchers, seeking perspectives that extend standard class-room fare. |
| data analysis real estate: GIS for Housing and Urban Development National Research Council, Division on Earth and Life Studies, Board on Earth Sciences and Resources, Committee on Geography, Committee on Review of Geographic Information Systems Research and Applications at HUD: Current Programs and Future Prospects, 2003-02-26 The report describes potential applications of geographic information systems (GIS) and spatial analysis by HUD's Office of Policy Development and Research for understanding housing needs, addressing broader issues of urban poverty and community development, and improving access to information and services by the many users of HUD's data. It offers a vision of HUD as an important player in providing urban data to federal initiatives towards a spatial data infrastructure for the nation. |
| data analysis real estate: Data Analytics for Accounting Vernon J. Richardson, Ryan Teeter, Katie L. Terrell, 2018-05-23 |
| data analysis real estate: Cognitive Analytics: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2020-03-06 Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians. |
| data analysis real estate: Assessing China’s Residential Real Estate Market Ding Ding, Xiaoyu Huang, Tao Jin, W. Raphael Lam, 2017-11-16 China’s real estate market rebounded sharply after a temporary slowdown in 2014-2015. This paper uses city-level data to estimate the range of house price overvaluation across city-tiers and assesses the main risks of a sharp housing market slowdown. If house prices rise further beyond “fundamental” levels and the bubble expands to smaller cities, it would increase the likelihood and costs of a sharp correction, which would weaken growth, undermine financial stability, reduce local government spending room, and spur capital outflows. Empirical analysis suggests that the increasing intensity of macroprudential policies tailored to local conditions is appropriate. The government should expand its toolkit to include additional macroprudential measures and push forward reforms to address the fundamental imbalances in the residential housing market. |
| data analysis real estate: ICEMBDA 2023 Jianguo Liu, Haifeng Li, Sikandar Ali Qalati, 2024-01-19 The 4th International Conference on Economic Management and Big Data Applications was successfully held in Tianjin, China from October 27th to 29th, 2023. This conference served as a platform for researchers, scholars, and industry professionals to exchange knowledge and insights in the field of economic management and the application of big data. The conference held great significance in advancing the understanding and application of economic management and big data. By bringing together experts from around the globe, the conference facilitated the exchange of innovative ideas and research findings, contributing to the development of these fields. The topics covered during the conference showcased the latest advancements and trends in enterprise economic statistics, information evaluation, blockchain technology, industrial structure optimization, information retrieval, data regression analysis, intelligent Internet of Things platforms, and data encryption. The discussions and presentations during the conference allowed participants to explore new methodologies, strategies, and technologies that can enhance economic management practices and leverage the potential of big data. The conference provided a platform for scholars and practitioners to share their experiences, insights, and best practices, fostering collaboration and networking opportunities. Furthermore, the proceedings were published, ensuring the dissemination of valuable research findings to a wider audience. The collective knowledge and research presented at the conference will contribute to the academic community, industry professionals, and policymakers, enabling them to make informed decisions and develop effective strategies in the fields of economic management and big data applications. Overall, the 4th International Conference on Economic Management and Big Data Applications played a pivotal role in promoting knowledge exchange, fostering innovation, and shaping the future of economic management by harnessing the power of big data. |
| data analysis real estate: The Dictionary of Real Estate Appraisal , 2002 This reference book defines hundreds of terms related to buildings, properties, markets, regulations, and appraisal. Specialized sections cover property types, business valuation, international valuation, real estate organizations and professional designations, legal and regulatory aspects, uniform standards, information technology, measures and conversions, and architecture and construction. The architecture and construction section is heavily illustrated with black-and-white photographs and diagrams. Annotation copyrighted by Book News, Inc., Portland, OR. |
| data analysis real estate: Valuation and management of Real Estate Liala Baiardi, 2018-03-30 The success of qualified and professional resources, the development of new approaches and methodologies in the real estate have already provided positive results, in terms of better quality offer of the proprieties. In a fully evolved market, in fact, the adherence by professionals to a specific code of conduct and the spread of shared procedures acknowledged as standards, represent a guarantee for quality. The experts must be able to compete on international markets in the field of technical and of economic management of existing buildings and urban environments. The main scope of this text is to provide methods and tools to be used for technical-economic evaluation on purchase or managing and valorize of building and property. In particular, it is addressed to those profiles in the real estate market and to the students that aim at a potential employment gravitating around the economic-financial management. This scope is achieved through formative procedures that include the description of the main processes and instruments that characterized the real estate operations worldwide. The main methodologies refer to the ones adopted by the operators of this sector and to the most common texts that include scientific publications, rule and codes widespread on a national and international scale. |
| data analysis real estate: Rough Sets Mengjun Hu, |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
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Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and …
Belmont Forum Adopts Open Data Principles for Environmental Chan…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
