The Historical Community and the Digital Future
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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 -
Digitalizing Historical Collections Through Data Bases- Digital Applications Towards Promotion of Historical Research
IOSR Journal Of Humanities And Social Science (IOSR-JHSS) e-ISSN: 2279-0837, p-ISSN: 2279-0845. PP 01-04 www.iosrjournals.org Digitalizing Historical Collections through Data Bases- Digital Applications towards Promotion of Historical Research Dr. Vidya .H.N Associate Professor Department of History Government Arts , Commerce and Post Graduate College Hassan-573201 Karnataka state [email protected], 9448870802 Abstract: This paper examines the emerging trends of application of digital tools to historical research and focuses on introducing digital training towards making historical research reach youth. Digital history is an approach to examine and representing the past that works with the new communication technologies of the computer internet network and software systems. It is an open arena of scholarly production and communication encompassing the development of new course materials and scholarly data collection efforts. Hence a digital historian encounters research issues relating to collection of historical sources, management of historical sources , exploration of historical sources , manipulation of historical sources and proper collaboration of historical sources. Hence there is a need to adopt a careful and completely informed approach in the use of digital tools for historical research. There is a need for a long term policy framework to develop new initiatives through training to historical scholars. There is a need for developing in house expertise for managing digital historical research. History teachers need awareness in using them appropriately. This needs to be evolved as national policy as higher education sector can play a key role in the evolution of such a policy. Keywords: Digitalizing historical collections, data bases, digital applications , promotion of historical research I. -
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. -
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. -
Teaching the Voices of History Through Primary Sources and Historical Fiction: a Case Study of Teacher and Librarian Roles
Syracuse University SURFACE School of Information Studies - Dissertations School of Information Studies (iSchool) 2011 Teaching the Voices of History Through Primary Sources and Historical Fiction: A Case Study of Teacher and Librarian Roles Barbara K. Stripling Syracuse University Follow this and additional works at: https://surface.syr.edu/it_etd Recommended Citation Stripling, Barbara K., "Teaching the Voices of History Through Primary Sources and Historical Fiction: A Case Study of Teacher and Librarian Roles" (2011). School of Information Studies - Dissertations. 66. https://surface.syr.edu/it_etd/66 This Dissertation is brought to you for free and open access by the School of Information Studies (iSchool) at SURFACE. It has been accepted for inclusion in School of Information Studies - Dissertations by an authorized administrator of SURFACE. For more information, please contact [email protected]. ABSTRACT The ability to analyze alternative points of view and to empathize (understand the beliefs, attitudes and actions of another from the other’s perspective rather than from one’s own) are essential building blocks for learning in the 21 st century. Empathy for the human participants of historical times has been deemed by a number of educators as important for the development of historical understanding. The classroom teacher and the school librarian both have a prominent stake in creating educational experiences that foster the development of perspective, empathy, and understanding. This case study was designed to investigate the idea -
Enterprise Data Classification Using Semantic Web Technologies
Enterprise Data Classification Using Semantic Web Technologies David Ben-David1, Tamar Domany2, and Abigail Tarem2 1 Technion – Israel Institute of Technology, Haifa 32000, Israel [email protected] 2 IBM Research – Haifa, University Campus, Haifa 31905, Israel {tamar,abigailt}@il.ibm.com Abstract. Organizations today collect and store large amounts of data in various formats and locations. However they are sometimes required to locate all instances of a certain type of data. Good data classification allows marking enterprise data in a way that enables quick and efficient retrieval of information when needed. We introduce a generic, automatic classification method that exploits Semantic Web technologies to assist in several phases in the classification process; defining the classification requirements, performing the classification and representing the results. Using Semantic Web technologies enables flexible and extensible con- figuration, centralized management and uniform results. This approach creates general and maintainable classifications, and enables applying se- mantic queries, rule languages and inference on the results. Keywords: Semantic Techniques, RDF, Classification, modeling. 1 Introduction Organizations today collect and store large amounts of data in various formats and locations. The data is then consumed in many places, sometimes copied or cached several times, causing valuable and sensitive business information to be scattered across many enterprise data stores. When an organization is required to meet certain legal or regulatory requirements, for instance to comply with regulations or perform discovery during civil litigation, it becomes necessary to find all the places where the required data is located. For example, if in order to comply with a privacy regulation an organization is required to mask all Social Security Numbers (SSN) when delivering personal information to unauthorized entities, all the occurrences of SSN must be found. -
Web Semantics in Cloud Computing
International Journal of Scientific & Engineering Research, Volume 7, Issue 2, February-2016 ISSN 2229-5518 378 Review: Web Semantics in Cloud Computing Rupali A. Meshram, Assistant professor, CSE Department, PRMIT&R, Badnera Komal R. Hole, Assistant professor, CSE Department, PRMIT&R, Badnera Pranita P. Deshmukh, Assistant professor, CSE Department, PRMIT&R, Badnera Roshan A. karwa, Assistant professor, CSE Department, PRMIT&R, Badnera Abstract – on web service and the web services are more efficient This paper shows how cloud computing on the so as to attract more users. background of Semantic Web is going to important. Many cloud computing services are Cloud computing has become interesting area both in implementing on distributed web environment and academia and industry. Semantic Web has been an provides virtualized resources, which focuses on some important research area in academic and industrial aspects like the semantic ambiguity, distributed researchers. Many applications will need to work with semantic reasoning, distributed semantic models large amounts of data, one particular application would construction, distributed metadata storage, parallel certainly not exist without the capability of accessing and semantic computing, etc. It also introduces many real processing arbitrary amounts of metadata: search world applications like semantic analysis in science engines that locate the data and services that other computing, cloud resource discovery, accurate applications need. To solve this problem, semantic web advertise recommendation, and web context services used with cloud computing. In this paper we understanding in commercial services. present the use of well established semantic technologies The Semantic Web is gaining immense in Cloud computing. The purpose of this report is to give popularity. -
A Multimodal Approach for Automatic WS Semantic Annotation
MATAWS: A Multimodal Approach for Automatic WS Semantic Annotation Cihan Aksoy1,2, Vincent Labatut1, Chantal Cherifi1,3 and Jean-François Santucci3, 1 Galatasaray University, Computer Science Department, Ortaköy/İstanbul, Turkey 2 TÜBİTAK, Gebze/Kocaeli, Turkey 3 University of Corsica, Corte, France [email protected] Abstract. Many recent works aim at developing methods and tools for the processing of semantic Web services. In order to be properly tested, these tools must be applied to an appropriate benchmark, taking the form of a collection of semantic WS descriptions. However, all of the existing publicly available collections are limited by their size or their realism (use of randomly generated or resampled descriptions). Larger and realistic syntactic (WSDL) collections exist, but their semantic annotation requires a certain level of automation, due to the number of operations to be processed. In this article, we propose a fully automatic method to semantically annotate such large WS collections. Our approach is multimodal, in the sense it takes advantage of the latent semantics present not only in the parameter names, but also in the type names and structures. Concept-to-word association is performed by using Sigma, a mapping of WordNet to the SUMO ontology. After having described in details our annotation method, we apply it to the larger collection of real-world syntactic WS descriptions we could find, and assess its efficiency. Keywords: Web Service, Semantic Web, Semantic Annotation, Ontology, WSDL, OWL-S. 1 Introduction The semantic Web encompasses technologies which can make possible the generation of the kind of intelligent documents imagined ten years ago [1]. -
Introductory Digital History Training for Mid-Career Historians
Scholars as Students: Introductory Digital History Training for Mid-Career Historians Sharon M. Leon and Sheila A. Brennan, Co-Directors Roy Rosenzweig Center for History and New Media, George Mason University August 31, 2015 Table of Contents Overview 1 Rationale 1 Institute Goals 5 Application Process and Participant Selection 8 Staffing 11 Two Weeks in August 12 Evaluation 15 Post-Institute Activities 17 Looking Forward 18 Appendix A: Institute Team 20 Appendix B: Curriculum 21 Appendix C: Application and Evaluation Forms 63 Overview Mid-career college and university faculty generally have achieved a significant level of expertise in their field of study. At the same time, research suggests that experts may not be so clear about every step of the cognitive work they undertake to attack a new research question or problem. In fact, the more expert an individual is, the less easy it is for that person to surface their process and articulate it for someone else. Only by being consciously pushed to consider, reconsider, and articulate these methodological assumptions, can we open a flexible space for new approaches that can complicate and compliment existing habits of mind. Together, these ideas make up some of the underlying approach that the team at the Roy Rosenzweig Center for History and New Media (RRCHNM) at George Mason University (Mason) took to design and in conducting the Doing Digital History <http://history2014.doingdh.org/> (Doing DH) two-week intensive summer institute for mid-career American historians. Funded by the National Endowment for the Humanities (NEH) Office of Digital Humanities as an Institute for Advanced Topics in the Digital Humanities in August 2014 and under the direction of Sharon M. -
Semantic Computing
SEMANTIC COMPUTING Lecture 12: Ontology Learning: Introduction Dagmar Gromann International Center For Computational Logic TU Dresden, 19 December 2018 Overview • Defining ontology • Introduction to ontology learning Dagmar Gromann, 19 December 2018 Semantic Computing 2 What is an ontology? Dagmar Gromann, 19 December 2018 Semantic Computing 3 What is an ontology? • Ontology (no plural = uncountable): philosophical study of being (existence, reality, categories of beings, etc.) • ontology (ontologies = countable): “formal, explicit specification of shared conceptualizations.’ (Studer et al. 1998: 186) • computational artifact designed with a purpose in mind • represented in a formal language to allow for the processing, reusing, and sharing of knowledge among humans and machines Studer, Rudi, Benjamins, Richard V., and Fensel, Dieter (1998), ’Knowledge Engineering: Principles and Methods’, Data & Knowledge Engineering, 25 (1-2), 161-198. Dagmar Gromann, 19 December 2018 Semantic Computing 4 Specification? Formal? A formal, explicit specification of shared conceptualizations; ideally an ontology: • is a model of (some aspect of) the world • captures a shared understanding of the domain of interest, a shared conceptualization • defines a vocabulary relevant to the domain and interpreted the same way by different users • specifies the meaning of the vocabulary in an explicit manner and often in a formal specification language Two main parts: • structure of the model = set of axioms • particular objects and situations = set of instances Dagmar Gromann, -
Annual Meeting of the National Council on Public History
THE MIDDLE: WHERE DID WE COME FROM? WHERE ARE WE GOING? April 19-22, 2017 // Indianapolis, Indiana Annual Meeting of the National Council on Public History Aerial View of a Parade on Monument Circle, Bretzman Collection, Indiana Historical Society, P0338. IUPUI Graduate Program in Public History Established in 1984, the Graduate Program in Public History at Indiana University – Purdue University Indianapolis (IUPUI) trains historians in the research, analytical, and communications skills needed to apply their work in the public arena. Students benefit from a combination of classroom instruction and practical experiences that prepare them for a wide range of public history occupations. Campus adjacent to downtown Indianapolis, which serves as a learning laboratory for public history students. Program highlights include: • A nationally-recognized public history degree program, with opportunities for students to pursue additional qualifications and certifications in Library Science, Museum Studies, and Documentary Editing • Two academic years of half-time paid internships in local institutions provide significant practical training (interns also receive a substantial tuition remission and health insurance) • Situated near several long-time partner institutions and research repositories (including the Indiana Historical Society, Indiana State Library and Historical Bureau, and Eiteljorg Museum of American Indians and Western Art) Graduate public history courses include: Digital Humanities, Historical Administration, Historic Preservation, -
Exploiting Semantic Web Knowledge Graphs in Data Mining
Exploiting Semantic Web Knowledge Graphs in Data Mining Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Universit¨atMannheim presented by Petar Ristoski Mannheim, 2017 ii Dekan: Dr. Bernd Lübcke, Universität Mannheim Referent: Professor Dr. Heiko Paulheim, Universität Mannheim Korreferent: Professor Dr. Simone Paolo Ponzetto, Universität Mannheim Tag der mündlichen Prüfung: 15 Januar 2018 Abstract Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in that field are knowledge intensive and can often benefit from using additional knowledge from various sources. Therefore, many approaches have been proposed in this area that combine Semantic Web data with the data mining and knowledge discovery process. Semantic Web knowledge graphs are a backbone of many in- formation systems that require access to structured knowledge. Such knowledge graphs contain factual knowledge about real word entities and the relations be- tween them, which can be utilized in various natural language processing, infor- mation retrieval, and any data mining applications. Following the principles of the Semantic Web, Semantic Web knowledge graphs are publicly available as Linked Open Data. Linked Open Data is an open, interlinked collection of datasets in machine-interpretable form, covering most of the real world domains. In this thesis, we investigate the hypothesis if Semantic Web knowledge graphs can be exploited as background knowledge in different steps of the knowledge discovery process, and different data mining tasks. More precisely, we aim to show that Semantic Web knowledge graphs can be utilized for generating valuable data mining features that can be used in various data mining tasks.