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Metadata for Semantic and Social Applications
etadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008M will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web — the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Metadata for Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their Semantic and information in interoperable ways (”participatory metadata”) is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. Social Applications DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice. Edited by Jane Greenberg and Wolfgang Klas DC-2008 -
Information Technology Management 14
Information Technology Management 14 Valerie Bryan Practitioner Consultants Florida Atlantic University Layne Young Business Relationship Manager Indianapolis, IN Donna Goldstein GIS Coordinator Palm Beach County School District Information Technology is a fundamental force in • IT as a management tool; reshaping organizations by applying investment in • understanding IT infrastructure; and computing and communications to promote competi- • ȱǯ tive advantage, customer service, and other strategic ęǯȱǻȱǯȱǰȱŗşşŚǼ ȱȱ ȱ¢ȱȱȱ¢ǰȱȱ¢Ȃȱ not part of the steamroller, you’re part of the road. ǻ ȱǼ ȱ ¢ȱ ȱ ȱ ęȱ ȱ ȱ ¢ǯȱȱȱȱȱ ȱȱ ȱ- ¢ȱȱȱȱȱǯȱ ǰȱ What is IT? because technology changes so rapidly, park and recre- ation managers must stay updated on both technological A goal of management is to provide the right tools for ȱȱȱȱǯ ěȱ ȱ ě¢ȱ ȱ ȱ ȱ ȱ ȱ ȱȱȱȱ ȱȱȱǰȱȱǰȱ ȱȱȱȱȱȱǯȱȱȱȱ ǰȱȱȱȱ ȱȱ¡ȱȱȱȱ recreation organization may be comprised of many of terms crucial for understanding the impact of tech- ȱȱȱȱǯȱȱ ¢ȱ ȱ ȱ ȱ ȱ ǯȱ ȱ ȱ ȱ ȱ ȱ ǯȱ ȱ - ȱȱęȱȱȱ¢ȱȱȱȱ ¢ȱǻ Ǽȱȱȱȱ¢ȱ ȱȱȱȱ ǰȱ ȱ ȱ ȬȬ ȱ ȱ ȱ ȱȱǯȱȱȱȱȱ ¢ȱȱǯȱȱ ȱȱȱȱ ȱȱ¡ȱȱȱȱȱǻǰȱŗşŞśǼǯȱ ȱȱȱȱȱȱĞȱȱȱȱ ǻȱ¡ȱŗŚǯŗȱ Ǽǯ ě¢ȱȱȱȱǯ Information technology is an umbrella term Details concerning the technical terms used in this that covers a vast array of computer disciplines that ȱȱȱȱȱȱȬȬęȱ ȱȱ permit organizations to manage their information ǰȱ ȱ ȱ ȱ Ȭȱ ¢ȱ ǯȱ¢ǰȱȱ¢ȱȱȱ ȱȱ ǯȱȱȱȱȱȬȱ¢ȱ a fundamental force in reshaping organizations by applying ȱȱ ȱȱ ȱ¢ȱȱȱȱ investment in computing and communications to promote ȱȱ¢ǯȱ ȱȱȱȱ ȱȱ competitive advantage, customer service, and other strategic ȱ ǻȱ ȱ ŗŚȬŗȱ ęȱ ȱ DZȱ ęȱǻǰȱŗşşŚǰȱǯȱřǼǯ ȱ Ǽǯ ȱ¢ȱǻ Ǽȱȱȱȱȱ ȱȱȱęȱȱȱ¢ȱȱ ȱ¢ǯȱȱȱȱȱ ȱȱ ȱȱ ȱȱȱȱ ȱ¢ȱ ȱȱǯȱ ȱ¢ǰȱ ȱȱ ȱDZ ȱȱȱȱǯȱ ȱȱȱȱǯȱ It lets people learn things they didn’t think they could • ȱȱȱ¢ǵ ȱǰȱȱǰȱȱȱǰȱȱȱȱȱǯȱ • the manager’s responsibilities; ǻȱǰȱȱ¡ȱĜȱȱĞǰȱȱ • information resources; ǷȱǯȱȱȱřŗǰȱŘŖŖŞǰȱ • disaster recovery and business continuity; ȱĴDZȦȦ ǯ ǯǼ Information Technology Management 305 Exhibit 14. -
Bioinformatics 1
Bioinformatics 1 Bioinformatics School School of Science, Engineering and Technology (http://www.stmarytx.edu/set/) School Dean Ian P. Martines, Ph.D. ([email protected]) Department Biological Science (https://www.stmarytx.edu/academics/set/undergraduate/biological-sciences/) Bioinformatics is an interdisciplinary and growing field in science for solving biological, biomedical and biochemical problems with the help of computer science, mathematics and information technology. Bioinformaticians are in high demand not only in research, but also in academia because few people have the education and skills to fill available positions. The Bioinformatics program at St. Mary’s University prepares students for graduate school, medical school or entry into the field. Bioinformatics is highly applicable to all branches of life sciences and also to fields like personalized medicine and pharmacogenomics — the study of how genes affect a person’s response to drugs. The Bachelor of Science in Bioinformatics offers three tracks that students can choose. • Bachelor of Science in Bioinformatics with a minor in Biology: 120 credit hours • Bachelor of Science in Bioinformatics with a minor in Computer Science: 120 credit hours • Bachelor of Science in Bioinformatics with a minor in Applied Mathematics: 120 credit hours Students will take 23 credit hours of core Bioinformatics classes, which included three credit hours of internship or research and three credit hours of a Bioinformatics Capstone course. BS Bioinformatics Tracks • Bachelor of Science -
From the Semantic Web to Social Machines
ARTICLE IN PRESS ARTINT:2455 JID:ARTINT AID:2455 /REV [m3G; v 1.23; Prn:25/11/2009; 12:36] P.1 (1-6) Artificial Intelligence ••• (••••) •••–••• Contents lists available at ScienceDirect Artificial Intelligence www.elsevier.com/locate/artint From the Semantic Web to social machines: A research challenge for AI on the World Wide Web ∗ Jim Hendler a, , Tim Berners-Lee b a Tetherless World Constellation, RPI, United States b Computer Science and AI Laboratory, MIT, United States article info abstract Article history: The advent of social computing on the Web has led to a new generation of Web Received 24 September 2009 applications that are powerful and world-changing. However, we argue that we are just Received in revised form 1 October 2009 at the beginning of this age of “social machines” and that their continued evolution and Accepted 1 October 2009 growth requires the cooperation of Web and AI researchers. In this paper, we show how Available online xxxx the growing Semantic Web provides necessary support for these technologies, outline the challenges we see in bringing the technology to the next level, and propose some starting places for the research. © 2009 Elsevier B.V. All rights reserved. Much has been written about the profound impact that the World Wide Web has had on society. Yet it is primarily in the past few years, as more interactive “read/write” technologies (e.g. Wikis, blogs and photo/video sharing) and social network- ing sites have proliferated, that the truly profound nature of this change is being felt. From the very beginning, however, the Web was designed to create a network of humans changing society empowered using this shared infrastructure. -
First-Order Logic
INF5390 – Kunstig intelligens First-Order Logic Roar Fjellheim Outline Logical commitments First-order logic First-order inference Resolution rule Reasoning systems Summary Extracts from AIMA Chapter 8: First-Order Logic Chapter 9: Inference in First-Order Logic INF5390-AI-05 First-Order Logic 2 From propositonal to first-order logic Features of propositional logic: + Declarative + Compositional + ”Possible-world” semantics - Lacks expressiveness First-order logic: Extends propositional logic Keeps good features Adds expressiveness INF5390-AI-05 First-Order Logic 3 First-order logic First-order logic is based on “common sense” or linguistic concepts: Objects: people, houses, numbers, .. Properties: tall, red, .. Relations: brother, bigger than, .. Functions: father of, roof of, .. Variables: x, y, .. (takes objects as values) First-order logic is the most important and best understood logic in philosophy, mathematics, and AI INF5390-AI-05 First-Order Logic 4 Logic “commitments” Ontological commitment Ontology - in philosophy, the study of “what is” What are the underlying assumptions of the logic with respect to the nature of reality Epistemological commitment Epistemology - in philosophy, the study of “what can be known” What are the underlying assumptions of the logic with respect to the nature of what the agent can know INF5390-AI-05 First-Order Logic 5 Commitments of some logic languages Language Ontological Epistemological Commitment Commitment Propositional logic Facts True/false/unknown First-order logic -
How to Keep a Knowledge Base Synchronized with Its Encyclopedia Source
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) How to Keep a Knowledge Base Synchronized with Its Encyclopedia Source Jiaqing Liang12, Sheng Zhang1, Yanghua Xiao134∗ 1School of Computer Science, Shanghai Key Laboratory of Data Science Fudan University, Shanghai, China 2Shuyan Technology, Shanghai, China 3Shanghai Internet Big Data Engineering Technology Research Center, China 4Xiaoi Research, Shanghai, China [email protected], fshengzhang16,[email protected] Abstract However, most of these knowledge bases tend to be out- dated, which limits their utility. For example, in many knowl- Knowledge bases are playing an increasingly im- edge bases, Donald Trump is only a business man even af- portant role in many real-world applications. How- ter the inauguration. Obviously, it is important to let ma- ever, most of these knowledge bases tend to be chines know that Donald Trump is the president of the United outdated, which limits the utility of these knowl- States so that they can understand that the topic of an arti- edge bases. In this paper, we investigate how to cle mentioning Donald Trump is probably related to politics. keep the freshness of the knowledge base by syn- Moreover, new entities are continuously emerging and most chronizing it with its data source (usually ency- of them are popular, such as iphone 8. However, it is hard for clopedia websites). A direct solution is revisiting a knowledge base to cover these entities in time even if the the whole encyclopedia periodically and rerun the encyclopedia websites have already covered them. entire pipeline of the construction of knowledge freshness base like most existing methods. -
Information Technology Manager Is a Professional Technical Stand Alone Class
CITY OF GRANTS PASS, OREGON CLASS SPECIFICATION FLSA Status : Exempt Bargaining Unit : Non-Bargaining INFORMATION TECHNOLOGY Salary Grade : UD2 MANAGER CLASS SUMMARY: The Information Technology Manager is a Professional Technical Stand Alone class. Incumbents are responsible for management of specific applications, computer hardware and software, and development of systems based on detailed specifications. Incumbents apply a broad knowledge base of programming code to City issues and work with systems that link to multiple databases involving complex equations. Based upon assignment, incumbents may manage small information technology projects. The Information Technology Manager is responsible for the full range of supervisory duties including directing work, training and coaching, discipline, and performance evaluation. CORE COMPETENCIES: Integrity/Accountability: Conducts oneself in a manner that is ethical, trustworthy and professional; demonstrates transparency with honest, responsive communication; behaves in a manner that supports the needs of Council, the citizens and co-workers; and conducts oneself in manner that supports the vision and goals of the organization taking pride in being engaged in the community. Vision: Actively seeks to discover and create ways of doing things better using resources and skills in an imaginative and innovative manner; encourages others to find solutions and contributes, regardless of responsibilities, to achieve a common goal; and listens and is receptive to different ideas and opinions while solving problems. Leadership/United: Focuses on outstanding results of the betterment of the individual, the organization and the community; consistently seeks opportunities for coordination and collaboration, working together as a team; displays an ability to adjust as needed to accomplish the common goal and offers praise when a job is done well. -
Learning Ontologies from RDF Annotations
/HDUQLQJÃRQWRORJLHVÃIURPÃ5')ÃDQQRWDWLRQV $OH[DQGUHÃ'HOWHLOÃ&DWKHULQHÃ)DURQ=XFNHUÃ5RVHÃ'LHQJ ACACIA project, INRIA, 2004, route des Lucioles, B.P. 93, 06902 Sophia Antipolis, France {Alexandre.Delteil, Catherine.Faron, Rose.Dieng}@sophia.inria.fr $EVWUDFW objects, as in [Mineau, 1990; Carpineto and Romano, 1993; Bournaud HWÃDO., 2000]. In this paper, we present a method for learning Since all RDF annotations are gathered inside a common ontologies from RDF annotations of Web RDF graph, the problem which arises is the extraction of a resources by systematically generating the most description for a given resource from the whole RDF graph. specific generalization of all the possible sets of After a brief description of the RDF data model (Section 2) resources. The preliminary step of our method and of RDF Schema (Section 3), Section 4 presents several consists in extracting (partial) resource criteria for extracting partial resource descriptions. In order descriptions from the whole RDF graph gathering to deal with the intrinsic complexity of the building of a all the annotations. In order to deal with generalization hierarchy, we propose an incremental algorithmic complexity, we incrementally build approach by gradually increasing the size of the descriptions the ontology by gradually increasing the size of the resource descriptions we consider. we consider. The principle of the approach is explained in Section 5 and more deeply detailed in Section 6. Ã ,QWURGXFWLRQ Ã 7KHÃ5')ÃGDWDÃPRGHO The Semantic Web, expected to be the next step that will RDF is the emerging Web standard for annotating resources lead the Web to its full potential, will be based on semantic HWÃDO metadata describing all kinds of Web resources. -
A New Generation Digital Content Service for Cultural Heritage Institutions
A New Generation Digital Content Service for Cultural Heritage Institutions Pierfrancesco Bellini, Ivan Bruno, Daniele Cenni, Paolo Nesi, Michela Paolucci, and Marco Serena Distributed Systems and Internet Technology Lab, DISIT, Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Firenze, Italy [email protected] http://www.disit.dsi.unifi.it Abstract. The evolution of semantic technology and related impact on internet services and solutions, such as social media, mobile technologies, etc., have de- termined a strong evolution in digital content services. Traditional content based online services are leaving the space to a new generation of solutions. In this paper, the experience of one of those new generation digital content service is presented, namely ECLAP (European Collected Library of Artistic Perform- ance, http://www.eclap.eu). It has been partially founded by the European Commission and includes/aggregates more than 35 international institutions. ECLAP provides services and tools for content management and user network- ing. They are based on a set of newly researched technologies and features in the area of semantic computing technologies capable of mining and establishing relationships among content elements, concepts and users. On this regard, ECLAP is a place in which these new solutions are made available for inter- ested institutions. Keywords: best practice network, semantic computing, recommendations, automated content management, content aggregation, social media. 1 Introduction Traditional library services in which the users can access to content by searching and browsing on-line catalogues obtaining lists of references and sporadically digital items (documents, images, etc.) are part of our history. With the introduction of web2.0/3.0, and thus of data mining and semantic computing, including social media and mobile technologies most of the digital libraries and museum services became rapidly obsolete and were constrained to rapidly change. -
Ontological Commitment of Natural Language Semantics
Ontological Commitment of Natural Language Semantics MSc Thesis (Afstudeerscriptie) written by Viktoriia Denisova (born July, 23d 1986 in Kustanay, Kazakhstan) under the supervision of Prof. Dr. Martin Stokhof, and submitted to the Board of Examiners in partial fulfillment of the requirements for the degree of MSc in Logic at the Universiteit van Amsterdam. Date of the public defense: Members of the Thesis Committee: March, 23d 2012 Prof. Dr. Martin Stokhof Prof. Dr. Frank Veltman Dr. Paul Dekker Contents Acknowledgments v Abstract vi Introduction 1 1 Quine's Ontological Criterion 5 1.1 Why do we need to define the criterion of ontological commitment? 5 1.2 Why do we operate on the semantic level when talking about on- tology? . 13 1.3 What does Quine's ontological criterion bring to semantics? . 15 1.4 What is the role of logic in determination of the ontological com- mitment? . 17 1.5 Concluding remarks . 19 2 Critique of the Ontological Criterion 21 2.1 Hodges on the philosophical importance of ontological commitment 21 2.2 Evaluation of Hodges's exposition . 25 2.3 Beyond the semantics of standard first-order logic . 27 2.3.1 The difficulties concerning first-order regimentation . 27 2.3.2 Regimentation of the sentences that contain plurals . 30 2.3.3 Regimentation of modals . 31 2.4 Evaluation of Rayo's exposition . 33 3 Ontological commitment within possible worlds semantics 35 3.1 The reasons to consider ontological commitment in intensional lan- guage . 35 3.2 Ontological commitment for proper names . 37 3.3 Natural kind terms . -
Automated Ontology Creation Using XML Schema Elements
Automated Ontology Creation using XML Schema Elements Samuel Suhas Singapogu, Paulo C. G. Costa, J. Mark Pullen C4I center, George Mason University Fairfax, VA, USA [ssingapo,pcosta,mpullen]@c4i.gmu.edu Abstract—Ontologies are commonly used to represent formal semantics in a computer system, usually capturing them in the Although ontologies are valuable assets in system model- form of concepts, relationships and axioms. Axioms convey ing, testing and analysis, the process of manually creating an asserted knowledge and support inferring new knowledge ontology for a complex system is inherently tedious and through logical reasoning. For complex systems, the process of error prone. Existing methods of knowledge discovery and creating ontologies manually can be tedious and error-prone. ontology creation usually are based on text mining of a data Many automated methods of knowledge discovery are based on mining domain text corpus, but current state-of-the-art meth- corpus for that domain. XML-based systems capture the ods using this approach fail to consider properly semantic data structure and syntax of all necessary and meaningful ele- embedded in XML schemata in complex systems. This paper ments in a XML schema, which therefore is a useful starting proposes a mapping method for identifying relevant semantic point for semantic analysis. In such systems, XML schemata data in XML schemata, automatically structuring and repre- have been shown to be a valuable resource of semantic data senting it in the form of a draft ontology. Concepts, concept [2]. Command and Control systems in the military context hierarchy and domain relationships from XML schema are support various functions, including commanding of forces mapped to relevant parts of an OWL ontology. -
An Academic Discipline
Information Technology – An Academic Discipline This document represents a summary of the following two publications defining Information Technology (IT) as an academic discipline. IT 2008: Curriculum Guidelines for Undergraduate Degree Programs in Information Technology. (Nov. 2008). Association for Computing Machinery (ACM) and IEEE Computer Society. Computing Curricula 2005 Overview Report. (Sep. 2005). Association for Computing Machinery (ACM), Association for Information Systems (AIS), Computer Society (IEEE- CS). The full text of these reports with details on the model IT curriculum and further explanation of the computing disciplines and their commonalities/differences can be found online: http://www.acm.org/education/education/curricula-recommendations) From IT 2008: Curriculum Guidelines for Undergraduate Degree Programs in Information Technology IT programs aim to provide IT graduates with the skills and knowledge to take on appropriate professional positions in Information Technology upon graduation and grow into leadership positions or pursue research or graduate studies in the field. Specifically, within five years of graduation a student should be able to: 1. Explain and apply appropriate information technologies and employ appropriate methodologies to help an individual or organization achieve its goals and objectives; 2. Function as a user advocate; 3. Manage the information technology resources of an individual or organization; 4. Anticipate the changing direction of information technology and evaluate and communicate the likely utility of new technologies to an individual or organization; 5. Understand and, in some cases, contribute to the scientific, mathematical and theoretical foundations on which information technologies are built; 6. Live and work as a contributing, well-rounded member of society. In item #2 above, it should be recognized that in many situations, "a user" is not a homogeneous entity.