Academic literature on the topic 'Transparency and data for valuation'
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Journal articles on the topic "Transparency and data for valuation"
Grover, Richard. "Mass valuations." Journal of Property Investment & Finance 34, no. 2 (March 7, 2016): 191–204. http://dx.doi.org/10.1108/jpif-01-2016-0001.
Full textHeller, J., and Daria Zlachevskaia. "Is it possible to improve methods of intellectual property valuation?" Zeszyty Teoretyczne Rachunkowości 45, no. 2 (June 21, 2021): 161–86. http://dx.doi.org/10.5604/01.3001.0014.9568.
Full textRaslanas, Saulius, and Laura Tupenaite. "PECULIARITIES OF PRIVATE HOUSES VALUATION BY SALES COMPARISON APPROACH." Technological and Economic Development of Economy 11, no. 4 (December 31, 2005): 233–41. http://dx.doi.org/10.3846/13928619.2005.9637703.
Full textRobinson, Angela, Anne E. Spencer, José Luís Pinto-Prades, and Judith A. Covey. "Exploring Differences between TTO and DCE in the Valuation of Health States." Medical Decision Making 37, no. 3 (September 27, 2016): 273–84. http://dx.doi.org/10.1177/0272989x16668343.
Full textLim, Audrey Li Chin, and Wong Wai Wai. "Embracing Blockchain Applications in Fundamental Analysis for Investment Management." Asia Proceedings of Social Sciences 2, no. 2 (December 3, 2018): 111–14. http://dx.doi.org/10.31580/apss.v2i2.370.
Full textSchröter, Matthias, Emilie Crouzat, Lisanne Hölting, Julian Massenberg, Julian Rode, Mario Hanisch, Nadja Kabisch, et al. "Assumptions in ecosystem service assessments: Increasing transparency for conservation." Ambio 50, no. 2 (September 11, 2020): 289–300. http://dx.doi.org/10.1007/s13280-020-01379-9.
Full textCoslor, Erica. "Transparency in an opaque market: Evaluative frictions between “thick” valuation and “thin” price data in the art market." Accounting, Organizations and Society 50 (April 2016): 13–26. http://dx.doi.org/10.1016/j.aos.2016.03.001.
Full textDennis, Sean A., Jeremy B. Griffin, and Karla M. Zehms. "The Value Relevance of Managers' and Auditors' Disclosures About Material Measurement Uncertainty." Accounting Review 94, no. 4 (September 1, 2018): 215–43. http://dx.doi.org/10.2308/accr-52272.
Full textGanesh, Maya Indira. "Entanglement." A Peer-Reviewed Journal About 6, no. 1 (April 1, 2017): 76–87. http://dx.doi.org/10.7146/aprja.v6i1.116013.
Full textStone, Patricia W., Richard H. Chapman, Eileen A. Sandberg, Bengt Liljas, and Peter J. Neumann. "MEASURING COSTS IN COST-UTILITY ANALYSES." International Journal of Technology Assessment in Health Care 16, no. 1 (January 2000): 111–24. http://dx.doi.org/10.1017/s0266462300161100.
Full textDissertations / Theses on the topic "Transparency and data for valuation"
Ineza, Kayihura Didier. "Adoption of Artificial Intelligence in Commercial Real Estate : Data Challenges, Transparency and Implications for Property Valuations." Thesis, KTH, Fastigheter och byggande, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298074.
Full textInvesteringsbeslut på fastighetsmarknaden är sammankopplat till fastighetsvärdering. Således är noggrannhet i värderingsresultat och en djup marknadsanalys nödvändiga. Artificiell intelligens (AI) modeller applicerades framgångsrikt inom olika områden och marknader. Fastighetsmarknaden är dock försenad i tid för att anpassa sig till dessa förändringar. Svenskt kommersiellt fastighetsmarknadsarrangemang är känd för ökad sekretess för vissa datatyper. Som en följd av detta minskar adopteringen av AI-värderingsmodeller på den svenska kommersiella fastighetsmarknaden. Denna studie syftar på att fylla i gapet i befintlig forskning genom att fokusera på marknadsaktörens beteende i förhållande till marknadsutveckling och utnyttja de möjligheter som ligger i adopteringen av AI-modeller i kommersiella fastighetsvärderingar.Den kvalitativa metoden baserad på intervjuer med experter har använts för att uppnå huvudmålet för denna studie. Resultaten tyder på att AI-värderingsmodellerna som används på kommersiella fastigheter tillämpas på värderingsdata och inte på transaktionsdata. Analysen täcker olika aspekter, inklusive datautmaningar och dess avslöjande, myndigheternas roll, marknads- och dataperspektiv för AI-tillämpning på fastighetsvärderingar. Ett ramverk för AI-implikationer i fastighetsvärdering inom olika tidshorisonter som presenteras i denna studie kommer att hjälpa till att överkomma datautmaningar och förbättra transparensen i värderingsresultaten. Denna studie är nyttig för olika aktörer på fastighetsmarknaden, inklusive myndigheter, investerare, värderare och forskare.
Sciuto, Alex. "Data Visualization for Medical Price Education and Transparency." Research Showcase @ CMU, 2015. http://repository.cmu.edu/theses/94.
Full textJackson, Kirsti. "Qualitative methods, transparency, and qualitative data analysis software| Toward an understanding of transparency in motion." Thesis, University of Colorado at Boulder, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3621346.
Full textThis study used in-depth, individual interviews to engage seven doctoral students and a paired member of their dissertation committee in discussions about qualitative research transparency and the use of NVivo, a Qualitative Data Analysis Software (QDAS), in pursuing it. The study also used artifacts (an exemplary qualitative research article of the participant's choice and the student's written dissertation) to examine specific researcher practices within particular contexts. The design and analysis were based on weak social constructionist (Schwandt, 2007), boundary object (Star, 1989; Star & Griesemer, 1989) and boundary-work (Gieryn, 1983, 1999) perspectives to facilitate a focus on: 1) The way transparency was used to coordinate activity in the absence of consensus. 2) The discursive strategies participants employed to describe various camps (e.g., qualitative and quantitative researchers) and to simultaneously stake claims to their understanding of transparency.
The analysis produced four key findings. First, the personal experiences of handling their qualitative data during analysis influenced the students' pursuit of transparency, long before any consideration of being transparent in the presentation of findings. Next, the students faced unpredictable issues when pursuing transparency, to which they responded in situ, considering a wide range of contextual factors. This was true even when informed by ideal types (Star & Griesemer, 1989) such as the American Educational Research Association (2006) guidelines that provided a framework for pursuing the principle of transparency. Thirdly, the QDAS-enabled visualizations students used while working with NVivo to interpret the data were described as a helpful (and sometimes indispensable) aspect of pursuing transparency. Finally, this situational use of visualizations to pursue transparency was positioned to re-examine, verify, and sometimes challenge their interpretations of their data over time as a form of self-interrogation, with less emphasis on showing their results to an audience. Together, these findings lead to a new conceptualization of transparency in motion, a process of tacking back and forth between situated practice of transparency and transparency as an ideal type. The findings also conclude with several proposals for advancing a transparency pedagogy. These proposals are provided to help qualitative researchers move beyond the often implicit, static, and post-hoc invocations of transparency in their work.
Nevitt, S. J. "Data sharing and transparency : the impact on evidence synthesis." Thesis, University of Liverpool, 2017. http://livrepository.liverpool.ac.uk/3017585/.
Full textHudson, Sara P. "Using contingent valuation data to simulate referendums." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-03302010-020112/.
Full textNicholson, Alexander Abu-Mostafa Yaser S. "Generalization error estimates and training data valuation /." Diss., Pasadena, Calif. : California Institute of Technology, 2002. http://resolver.caltech.edu/CaltechETD:etd-09062005-083717.
Full textRowley, Steven. "A National Valuation Evidence Database : the future of valuation data provision and collection." Thesis, Northumbria University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245441.
Full textPulls, Tobias. "Preserving Privacy in Transparency Logging." Doctoral thesis, Karlstads universitet, Institutionen för matematik och datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-35918.
Full textThe subject of this dissertation is the construction of privacy-enhancing technologies (PETs) for transparency logging, a technology at the intersection of privacy, transparency, and accountability. Transparency logging facilitates the transportation of data from service providers to users of services and is therefore a key enabler for ex-post transparency-enhancing tools (TETs). Ex-post transparency provides information to users about how their personal data have been processed by service providers, and is a prerequisite for accountability: you cannot hold a controller accountable for what is unknown. We present three generations of PETs for transparency logging to which we contributed. We start with early work that defined the setting as a foundation and build upon it to increase both the privacy protections and the utility of the data sent through transparency logging. Our contributions include the first provably secure privacy-preserving transparency logging scheme and a forward-secure append-only persistent authenticated data structure tailored to the transparency logging setting. Applications of our work range from notifications and deriving data disclosures for the Data Track tool (an ex-post TET) to secure evidence storage.
Murmann, Patrick. "Towards Usable Transparency via Individualisation." Licentiate thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-71120.
Full textPaper 2 ingick som manuskript i avhandlingen, nu publicerad.
Bonatti, Piero A., Bert Bos, Stefan Decker, Garcia Javier David Fernandez, Sabrina Kirrane, Vassilios Peristeras, Axel Polleres, and Rigo Wenning. "Data Privacy Vocabularies and Controls: Semantic Web for Transparency and Privacy." CEUR Workshop Proceedings, 2018. http://epub.wu.ac.at/6490/1/SW4SG_2018.pdf.
Full textBooks on the topic "Transparency and data for valuation"
San Francisco (Calif.). Dept. of Building Inspection. Cost schedule: Building valuation data. San Francisco, Calif: Dept. of Building Inspection, 2002.
Find full textSan Francisco (Calif.). Dept. of Building Inspection. Cost schedule: Building valuation data. San Francisco, Calif: Dept. of Building Inspection, 2001.
Find full textSan Francisco (Calif.). Dept. of Building Inspection. Cost schedule: Building valuation data. San Francisco, Calif: Dept. of Building Inspection, 2003.
Find full textSchatt, Stanley. Solutions manual and transparency masters. New York: Macmillan, 1990.
Find full textKester, Anne Y. IMF data standards initiatives: A consultative approach to enhancing global data transparency. [Washington, D.C.]: International Monetary Fund, Statistics Dept., 2006.
Find full textJohn, Jones. Farm real estate historical series data, 1950. Washington, D.C: U.S. Dept. of Agriculture, Economic Research Service, 1985.
Find full textParadata and transparency in virtual heritage. Farnham, Surrey, England: Ashgate, 2012.
Find full textLandier, Augustin. Regulating systemic risk through transparency: Tradeoffs in making data public. Cambridge, MA: National Bureau of Economic Research, 2011.
Find full textMasci, Pietro, José Antonio Laínez Gadea, and Juan José Durante. International accounting standards: Transparency, disclosure and valuation for Latin America and the Caribbean. Washington, D.C: Inter-American Development Bank, 2004.
Find full textGreene, Catherine. U.S. farmland values, 1982-84: A comparison of experimental and traditional data. [Washington, D.C.]: U.S. Dept. of Agriculture, Economic Research Service, Natural Resource Economics Division, 1985.
Find full textBook chapters on the topic "Transparency and data for valuation"
Washington, Anne L. "Transparency." In Encyclopedia of Big Data, 1–4. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-32001-4_199-1.
Full textWashington, Anne L. "Transparency." In Encyclopedia of Big Data, 1–4. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-32001-4_199-2.
Full textSchöne, Max. "Data." In Real Options Valuation, 6–8. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-07493-7_2.
Full textLambert, Paul B. "Transparency." In Essential Introduction to Understanding European Data Protection Rules, 375–84. Boca Raton : CRC Press, 2017.: Auerbach Publications, 2017. http://dx.doi.org/10.1201/9781138069848-35.
Full textLambert, Paul B. "Transparency." In Essential Introduction to Understanding European Data Protection Rules, 375–84. Boca Raton : CRC Press, 2017.: Auerbach Publications, 2017. http://dx.doi.org/10.1201/9781315115269-35.
Full textWeik, Martin H. "data circuit transparency." In Computer Science and Communications Dictionary, 342. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4216.
Full textMoro Visconti, Roberto. "Big Data Valuation." In The Valuation of Digital Intangibles, 345–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36918-7_13.
Full textWang, Ze, Jingqiang Lin, Quanwei Cai, Qiongxiao Wang, Jiwu Jing, and Daren Zha. "Blockchain-Based Certificate Transparency and Revocation Transparency." In Financial Cryptography and Data Security, 144–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-58820-8_11.
Full textWeik, Martin H. "data signaling rate transparency." In Computer Science and Communications Dictionary, 358. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4375.
Full textSchnidman, Evan A., and William D. MacMillan. "Transparency: Data Meets Democracy." In How the Fed Moves Markets, 39–48. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/9781137432582_5.
Full textConference papers on the topic "Transparency and data for valuation"
Madala, D. S. V., Mahabir Prasad Jhanwar, and Anupam Chattopadhyay. "Certificate Transparency Using Blockchain." In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018. http://dx.doi.org/10.1109/icdmw.2018.00018.
Full textCorrêa, Andreiwid Sheffer, Pedro Luiz Pizzigatti Corrêa, and Flávio Soares Corrêa da Silva. "Transparency portals versus open government data." In the 15th Annual International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2612733.2612760.
Full textAngulo, Julio, Simone Fischer-Hübner, Tobias Pulls, and Erik Wästlund. "Usable Transparency with the Data Track." In CHI '15: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2702613.2732701.
Full textMa, Xiao, and Xu Zhang. "MDV: A Multi-Factors Data Valuation Method." In 2019 5th International Conference on Big Data Computing and Communications (BIGCOM). IEEE, 2019. http://dx.doi.org/10.1109/bigcom.2019.00016.
Full textSathananthan, Suthamathy. "Data valuation considering knowledge transformation, process models and data models." In 2018 12th International Conference on Research Challenges in Information Science (RCIS). IEEE, 2018. http://dx.doi.org/10.1109/rcis.2018.8406649.
Full textO'Hara, Kieron. "Transparency, open data and trust in government." In the 3rd Annual ACM Web Science Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2380718.2380747.
Full textBarreto, Patrick, Luciana Salgado, and José Viterbo. "Transparency Communication Strategies in Human-Data Interaction." In the XIV Brazilian Symposium. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3229345.3229414.
Full textHong, Sounman. "Electoral Competition, Transparency, and Open Government Data." In dg.o '20: The 21st Annual International Conference on Digital Government Research. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3396956.3398254.
Full textBaker, Michael, Jonathan Groff, Françoise Détienne, Jerry Andriessen, Mirjam Pardijs, Michael Hogan, Owen Harney, Erna Ruijer, and Vittorio Scarano. "Technology-supported effective transparency around open data." In ECCE 2017: European Conference on Cognitive Ergonomics 2017. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3121283.3121293.
Full textAbiteboul, Serge, Pierre Bourhis, and Victor Vianu. "Explanations and Transparency in Collaborative Workflows." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196959.3196975.
Full textReports on the topic "Transparency and data for valuation"
Head, Stephany J., and Julianne B. Nelson. Data Rights Valuation in Software Acquisitions. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada565798.
Full textLa Rosa, L., and T. Sandoval-Martín. The Transparency Law‘s insufficiency for Data Journalism‘s practices in Spain. Revista Latina de Comunicación Social, November 2016. http://dx.doi.org/10.4185/rlcs-2016-1142en.
Full textLa Rosa, L., and T. Sandoval-Martín. The Transparency Law‘s insufficiency for Data Journalism‘s practices in Spain. Revista Latina de Comunicación Social, November 2016. http://dx.doi.org/10.4185/rlcs-2016-1162en.
Full textLandier, Augustin, and David Thesmar. Regulating Systemic Risk through Transparency: Tradeoffs in Making Data Public. Cambridge, MA: National Bureau of Economic Research, December 2011. http://dx.doi.org/10.3386/w17664.
Full textKahn, Michael, Toan Ong, Juliana Barnard, and Julie Maertens. Building PCOR Value and Integrity with Data Quality and Transparency Standards. Patient-Centered Outcomes Research Institute (PCORI), March 2018. http://dx.doi.org/10.25302/3.2018.me.13035581.
Full textLudwig, Jens, and Philip Cook. The Benefits of Reducing Gun Violence: Evidence from Contingent-Valuation Survey Data. Cambridge, MA: National Bureau of Economic Research, June 1999. http://dx.doi.org/10.3386/w7166.
Full textBraguinsky, Serguey, and Sergey Mityakov. Foreign Corporations and the Culture of Transparency: Evidence from Russian Administrative Data. Cambridge, MA: National Bureau of Economic Research, January 2012. http://dx.doi.org/10.3386/w17731.
Full textUberhuaga, Patricia del Carmen, and Carsten Smith Olsen. Can we trust the data? : methodological experiences with forest product valuation in lowland Bolivia. Unknown, 2008. http://dx.doi.org/10.35648/20.500.12413/11781/ii123.
Full textParish, Simon, Marc J. Cohen, and Tigist Mekuria. Follow the Money: Using International Aid Transparency Initiative data to trace development aid flows to their end use. Oxfam; Development Initiatives, March 2018. http://dx.doi.org/10.21201/2017.1800.
Full textBenages, Eva, and Matilde Mas. Knowledge-Based Capital in a Set of Latin American Countries: The LA KLEMS-IADB Project. Inter-American Development Bank, April 2021. http://dx.doi.org/10.18235/0003202.
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