Geotagging Photos to Share Field Trips with the World During the Past Few
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Metadata and GIS
Metadata and GIS ® An ESRI White Paper • October 2002 ESRI 380 New York St., Redlands, CA 92373-8100, USA • TEL 909-793-2853 • FAX 909-793-5953 • E-MAIL [email protected] • WEB www.esri.com Copyright © 2002 ESRI All rights reserved. Printed in the United States of America. The information contained in this document is the exclusive property of ESRI. This work is protected under United States copyright law and other international copyright treaties and conventions. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording, or by any information storage or retrieval system, except as expressly permitted in writing by ESRI. All requests should be sent to Attention: Contracts Manager, ESRI, 380 New York Street, Redlands, CA 92373-8100, USA. The information contained in this document is subject to change without notice. U.S. GOVERNMENT RESTRICTED/LIMITED RIGHTS Any software, documentation, and/or data delivered hereunder is subject to the terms of the License Agreement. In no event shall the U.S. Government acquire greater than RESTRICTED/LIMITED RIGHTS. At a minimum, use, duplication, or disclosure by the U.S. Government is subject to restrictions as set forth in FAR §52.227-14 Alternates I, II, and III (JUN 1987); FAR §52.227-19 (JUN 1987) and/or FAR §12.211/12.212 (Commercial Technical Data/Computer Software); and DFARS §252.227-7015 (NOV 1995) (Technical Data) and/or DFARS §227.7202 (Computer Software), as applicable. Contractor/Manufacturer is ESRI, 380 New York Street, Redlands, CA 92373- 8100, USA. -
Creating Permissionless Blockchains of Metadata Records Dejah Rubel
Articles No Need to Ask: Creating Permissionless Blockchains of Metadata Records Dejah Rubel ABSTRACT This article will describe how permissionless metadata blockchains could be created to overcome two significant limitations in current cataloging practices: centralization and a lack of traceability. The process would start by creating public and private keys, which could be managed using digital wallet software. After creating a genesis block, nodes would submit either a new record or modifications to a single record for validation. Validation would rely on a Federated Byzantine Agreement consensus algorithm because it offers the most flexibility for institutions to select authoritative peers. Only the top tier nodes would be required to store a copy of the entire blockchain thereby allowing other institutions to decide whether they prefer to use the abridged version or the full version. INTRODUCTION Several libraries and library vendors are investigating how blockchain could improve activities such as scholarly publishing, content dissemination, and copyright enforcement. A few organizations, such as Katalysis, are creating prototypes or alpha versions of blockchain platforms and products.1 Although there has been some discussion about using blockchains for metadata creation and management, only one company appears to be designing such a product. Therefore, this article will describe how permissionless blockchains of metadata records could be created, managed, and stored to overcome current challenges with metadata creation and management. LIMITATIONS OF CURRENT PRACTICES Metadata standards, processes, and systems are changing to meet twenty-first century information needs and expectations. There are two significant limitations, however, to our current metadata creation and modification practices that have not been addressed: centralization and traceability. -
How to Find the Best Hashtags for Your Business Hashtags Are a Simple Way to Boost Your Traffic and Target Specific Online Communities
CHECKLIST How to find the best hashtags for your business Hashtags are a simple way to boost your traffic and target specific online communities. This checklist will show you everything you need to know— from the best research tools to tactics for each social media network. What is a hashtag? A hashtag is keyword or phrase (without spaces) that contains the # symbol. Marketers tend to use hashtags to either join a conversation around a particular topic (such as #veganhealthchat) or create a branded community (such as Herschel’s #WellTravelled). HOW TO FIND THE BEST HASHTAGS FOR YOUR BUSINESS 1 WAYS TO USE 3 HASHTAGS 1. Find a specific audience Need to reach lawyers interested in tech? Or music lovers chatting about their favorite stereo gear? Hashtags are a simple way to find and reach niche audiences. 2. Ride a trend From discovering soon-to-be viral videos to inspiring social movements, hashtags can quickly connect your brand to new customers. Use hashtags to discover trending cultural moments. 3. Track results It’s easy to monitor hashtags across multiple social channels. From live events to new brand campaigns, hashtags both boost engagement and simplify your reporting. HOW TO FIND THE BEST HASHTAGS FOR YOUR BUSINESS 2 HOW HASHTAGS WORK ON EACH SOCIAL NETWORK Twitter Hashtags are an essential way to categorize content on Twitter. Users will often follow and discover new brands via hashtags. Try to limit to two or three. Instagram Hashtags are used to build communities and help users find topics they care about. For example, the popular NYC designer Jessica Walsh hosts a weekly Q&A session tagged #jessicasamamondays. -
Studying Social Tagging and Folksonomy: a Review and Framework
Studying Social Tagging and Folksonomy: A Review and Framework Item Type Journal Article (On-line/Unpaginated) Authors Trant, Jennifer Citation Studying Social Tagging and Folksonomy: A Review and Framework 2009-01, 10(1) Journal of Digital Information Journal Journal of Digital Information Download date 02/10/2021 03:25:18 Link to Item http://hdl.handle.net/10150/105375 Trant, Jennifer (2009) Studying Social Tagging and Folksonomy: A Review and Framework. Journal of Digital Information 10(1). Studying Social Tagging and Folksonomy: A Review and Framework J. Trant, University of Toronto / Archives & Museum Informatics 158 Lee Ave, Toronto, ON Canada M4E 2P3 jtrant [at] archimuse.com Abstract This paper reviews research into social tagging and folksonomy (as reflected in about 180 sources published through December 2007). Methods of researching the contribution of social tagging and folksonomy are described, and outstanding research questions are presented. This is a new area of research, where theoretical perspectives and relevant research methods are only now being defined. This paper provides a framework for the study of folksonomy, tagging and social tagging systems. Three broad approaches are identified, focusing first, on the folksonomy itself (and the role of tags in indexing and retrieval); secondly, on tagging (and the behaviour of users); and thirdly, on the nature of social tagging systems (as socio-technical frameworks). Keywords: Social tagging, folksonomy, tagging, literature review, research review 1. Introduction User-generated keywords – tags – have been suggested as a lightweight way of enhancing descriptions of on-line information resources, and improving their access through broader indexing. “Social Tagging” refers to the practice of publicly labeling or categorizing resources in a shared, on-line environment. -
Geotagging: an Innovative Tool to Enhance Transparency and Supervision
Geotagging: An Innovative Tool To Enhance Transparency and Supervision Transparency through Geotagging Noel Sta. Ines Geotagging Geotagging • Process of assigning a geographical reference, i.e, geographical coordinates (latitude and longitude) + elevation - to an object. • This could be done by taking photos, nodes and tracks with recorded GPS coordinates. • This allows geo-tagged object or SP data to be easily and accurately located on a map. WhatThe is Use Geotagging and Implementation application in of the Geo Philippines?-Tagging • A revolutionary and inexpensive approach of using ICT + GPS applications for accurate visualization of sub-projects • Device required is only a GPS enabled android cellphone, and access to freely available apps • Easily replicable for mainstreaming to Government institutions & CSOs • Will help answer the question: Is the right activity implemented in the right place? – (asset verification tool) Geotagging: An Innovative Tool to Enhance Transparency and Supervision Geotagging Example No. 1: Visualization of a farm-to-market road in a conflict area: showing specific location, ground distance, track / alignment, elevation profile, ground photos (with coordinates, date and time taken) of Farm-to-market Road, i.e. baseline information + Progress photos + 3D visualization Geotagging: An Innovative Tool to Enhance Transparency and Supervision Geotagging Example No. 2: Location and Visualization of rehabilitation of a city road in Earthquake damaged-area in Tagbilaran, Bohol, Philippines by the auditors and the citizen volunteers Geotagging: An Innovative Tool to Enhance Transparency and Supervision Geo-tagging Example No. 3 Visualization of a water supply project showing specific location, elevation profile from the source , distribution lines and faucets, and ground photos of community faucets Geotagging: An Innovative Tool to Enhance Transparency and Supervision Geo-tagging Example No. -
Acceptable Use of Instant Messaging Issued by the CTO
State of West Virginia Office of Technology Policy: Acceptable Use of Instant Messaging Issued by the CTO Policy No: WVOT-PO1010 Issued: 11/24/2009 Revised: 12/22/2020 Page 1 of 4 1.0 PURPOSE This policy details the use of State-approved instant messaging (IM) systems and is intended to: • Describe the limitations of the use of this technology; • Discuss protection of State information; • Describe privacy considerations when using the IM system; and • Outline the applicable rules applied when using the State-provided system. This document is not all-inclusive and the WVOT has the authority and discretion to appropriately address any unacceptable behavior and/or practice not specifically mentioned herein. 2.0 SCOPE This policy applies to all employees within the Executive Branch using the State-approved IM systems, unless classified as “exempt” in West Virginia Code Section 5A-6-8, “Exemptions.” The State’s users are expected to be familiar with and to comply with this policy, and are also required to use their common sense and exercise their good judgment while using Instant Messaging services. 3.0 POLICY 3.1 State-provided IM is appropriate for informal business use only. Examples of this include, but may not be limited to the following: 3.1.1 When “real time” questions, interactions, and clarification are needed; 3.1.2 For immediate response; 3.1.3 For brainstorming sessions among groups; 3.1.4 To reduce chances of misunderstanding; 3.1.5 To reduce the need for telephone and “email tag.” 3.2 Employees must only use State-approved instant messaging. -
Metadata Creation Practices in Digital Repositories and Collections
Metadata Creation Practices in Digital Repositories and Collections: Schemata, Jung-ran Park and Selection Criteria, and Interoperability Yuji Tosaka This study explores the current state of metadata-creation development of such a mediation mechanism calls for practices across digital repositories and collections by an empirical assessment of various issues surrounding metadata-creation practices. using data collected from a nationwide survey of mostly The critical issues concerning metadata practices cataloging and metadata professionals. Results show across distributed digital collections have been rela- that MARC, AACR2, and LCSH are the most widely tively unexplored. While examining learning objects and used metadata schema, content standard, and subject- e-prints communities of practice, Barton, Currier, and Hey point out the lack of formal investigation of the metadata- controlled vocabulary, respectively. Dublin Core (DC) is creation process.2 As will be discussed in the following the second most widely used metadata schema, followed section, some researchers have begun to assess the current by EAD, MODS, VRA, and TEI. Qualified DC’s wider state of descriptive practices, metadata schemata, and use vis-à-vis Unqualified DC (40.6 percent versus 25.4 content standards. However, the literature has not yet developed to a point where it affords a comprehensive percent) is noteworthy. The leading criteria in selecting picture. Given the propagation of metadata projects, it is metadata and controlled-vocabulary schemata are collec- important to continue to track changes in metadata-cre- tion-specific considerations, such as the types of resources, ation practices while they are still in constant flux. Such efforts are essential for adding new perspectives to digital nature of the collection, and needs of primary users and library research and practices in an environment where communities. -
Geotag Propagation in Social Networks Based on User Trust Model
1 Geotag Propagation in Social Networks Based on User Trust Model Ivan Ivanov, Peter Vajda, Jong-Seok Lee, Lutz Goldmann, Touradj Ebrahimi Multimedia Signal Processing Group Ecole Polytechnique Federale de Lausanne, Switzerland Multimedia Signal Processing Group Swiss Federal Institute of Technology Motivation 2 We introduce users in our system for geotagging in order to simulate a real social network GPS coordinates to derive geographical annotation, which are not available for the majority of web images and photos A GPS sensor in a camera provides only the location of the photographer instead of that of the captured landmark Sometimes GPS and Wi-Fi geotagging determine wrong location due to noise http: //www.pl acecas t.net Multimedia Signal Processing Group Swiss Federal Institute of Technology Motivation 3 Tag – short textual annotation (free-form keyword)usedto) used to describe photo in order to provide meaningful information about it User-provided tags may sometimes be spam annotations given on purpose or wrong tags given by mistake User can be “an algorithm” http://code.google.com/p/spamcloud http://www.flickr.com/photos/scriptingnews/2229171225 Multimedia Signal Processing Group Swiss Federal Institute of Technology Goal 4 Consider user trust information derived from users’ tagging behavior for the tag propagation Build up an automatic tag propagation system in order to: Decrease the anno ta tion time, and Increase the accuracy of the system http://www.costadevault.com/blog/2010/03/listening-to-strangers Multimedia -
UC Berkeley International Conference on Giscience Short Paper Proceedings
UC Berkeley International Conference on GIScience Short Paper Proceedings Title Tweet Geolocation Error Estimation Permalink https://escholarship.org/uc/item/0wf6w9p9 Journal International Conference on GIScience Short Paper Proceedings, 1(1) Authors Holbrook, Erik Kaur, Gupreet Bond, Jared et al. Publication Date 2016 DOI 10.21433/B3110wf6w9p9 Peer reviewed eScholarship.org Powered by the California Digital Library University of California GIScience 2016 Short Paper Proceedings Tweet Geolocation Error Estimation E. Holbrook1, G. Kaur1, J. Bond1, J. Imbriani1, C. E. Grant1, and E. O. Nsoesie2 1University of Oklahoma, School of Computer Science Email: {erik; cgrant; gkaur; jared.t.bond-1; joshimbriani}@ou.edu 2University of Washington, Institute for Health Metrics and Evaluation Email: [email protected] Abstract Tweet location is important for researchers who study real-time human activity. However, few studies have examined the reliability of social media user-supplied location and description in- formation, and most who do use highly disparate measurements of accuracy. We examined the accuracy of predicting Tweet origin locations based on these features, and found an average ac- curacy of 1941 km. We created a machine learning regressor to evaluate the predictive accuracy of the textual content of these fields, and obtained an average accuracy of 256 km. In a dataset of 325788 tweets over eight days, we obtained city-level accuracy for approximately 29% of users based only on their location field. We describe a new method of measuring location accuracy. 1. Introduction With the rise of micro-blogging services and publicly available social media posts, the problem of location identification has become increasingly important. -
Geotagging with Local Lexicons to Build Indexes for Textually-Specified Spatial Data
Geotagging with Local Lexicons to Build Indexes for Textually-Specified Spatial Data Michael D. Lieberman, Hanan Samet, Jagan Sankaranarayanan Center for Automation Research, Institute for Advanced Computer Studies, Department of Computer Science, University of Maryland College Park, MD 20742, USA {codepoet, hjs, jagan}@cs.umd.edu Abstract— The successful execution of location-based and feature-based queries on spatial databases requires the construc- tion of spatial indexes on the spatial attributes. This is not simple when the data is unstructured as is the case when the data is a collection of documents such as news articles, which is the domain of discourse, where the spatial attribute consists of text that can be (but is not required to be) interpreted as the names of locations. In other words, spatial data is specified using text (known as a toponym) instead of geometry, which means that there is some ambiguity involved. The process of identifying and disambiguating references to geographic locations is known as geotagging and involves using a combination of internal document structure and external knowledge, including a document-independent model of the audience’s vocabulary of geographic locations, termed its Fig. 1. Locations mentioned in news articles about the May 2009 swine flu pandemic, obtained by geotagging related news articles. Large red circles spatial lexicon. In contrast to previous work, a new spatial lexicon indicate high frequency, and small circles are color coded according to recency, model is presented that distinguishes between a global lexicon of with lighter colors indicating the newest mentions. locations known to all audiences, and an audience-specific local lexicon. -
Geotagging Tweets Using Their Content
Proceedings of the Twenty-Fourth International Florida Artificial Intelligence Research Society Conference Geotagging Tweets Using Their Content Sharon Paradesi Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology [email protected] Abstract Harnessing rich, but unstructured information on social networks in real-time and showing it to relevant audi- ence based on its geographic location is a major chal- lenge. The system developed, TwitterTagger, geotags tweets and shows them to users based on their current physical location. Experimental validation shows a per- formance improvement of three orders by TwitterTag- ger compared to that of the baseline model. Introduction People use popular social networking websites such as Face- book and Twitter to share their interests and opinions with their friends and the online community. Harnessing this in- formation in real-time and showing it to the relevant audi- ence based on its geographic location is a major challenge. Figure 1: Architecture of TwitterTagger The microblogging social medium, Twitter, is used because of its relevance to users in real-time. The goal of this research is to identify the locations refer- Pipe POS tagger1. The noun phrases are then compared with enced in a tweet and show relevant tweets to a user based on the USGS database2 of locations. Common noun phrases, that user’s location. For example, a user traveling to a new such as ‘Love’ and ‘Need’, are also place names and would place would would not necessarily know all the events hap- be geotagged. To avoid this, the system uses a greedy ap- pening in that place unless they appear in the mainstream proach of phrase chunking. -
Tag Recommendations in Social Bookmarking Systems
1 Tag Recommendations in Social Bookmarking Systems Robert Jaschke¨ a,c Leandro Marinho b,d 1. Introduction Andreas Hotho a Lars Schmidt-Thieme b Gerd Stumme a,c Folksonomies are web-based systems that allow users to upload their resources, and to label them with a Knowledge & Data Engineering Group (KDE), arbitrary words, so-called tags. The systems can be dis- University of Kassel, tinguished according to what kind of resources are sup- 1 Wilhelmshoher¨ Allee 73, 34121 Kassel, Germany ported. Flickr , for instance, allows the sharing of pho- tos, del.icio.us2 the sharing of bookmarks, CiteULike3 http://www.kde.cs.uni-kassel.de 4 b and Connotea the sharing of bibliographic references, Information Systems and Machine Learning Lab and last.fm5 the sharing of music listening habits. Bib- (ISMLL), University of Hildesheim, 6 Sonomy allows to share bookmarks and BIBTEX based Samelsonplatz 1, 31141 Hildesheim, Germany publication entries simultaneously. http://www.ismll.uni-hildesheim.de In their core, these systems are all very similar. Once c Research Center L3S, a user is logged in, he can add a resource to the sys- Appelstr. 9a, 30167 Hannover, Germany tem, and assign arbitrary tags to it. The collection of all his assignments is his personomy, the collection of http://www.l3s.de folksonomy d all personomies constitutes the . The user Brazilian National Council Scientific and can explore his personomy, as well as the whole folk- Technological Research (CNPq) scholarship holder. sonomy, in all dimensions: for a given user one can see all resources he has uploaded, together with the tags he Abstract.