Spatiotemporal Infrastructure for Semantic Network in Digital Archives

1. Spatiotemporal Infrastructure for Semantic Network in Digital Archives Eric Yen Computing Centre, Academia Sinica Dec, 2002

2. Outline • Introduction • NDAP Approaches – Space-Time-Language Coordinates • Archiving and processing of millions of geospatial materials in AS • Characteristics • How to delve into the knowledge level • Experiences & Lessons we learned • Extend to more general solution • Geolibrary • The Trends • Conclusions

3. Introduction to Digital Archive • Digital Archive is a collection of digital objects. • A digital object is defined as something (e.g., an image, an audio recording, a text document, a movie, a map) that has been digitally encoded and integrated with metadata to support discovery, use, and storage of those objects. • Goals for Digital Archive (functional point of view) • Protection of the original • Duplication for safety • Search and Retrieval • Easy Access • Resource Sharing • Lower cost of maintenance and dissemination • Max. flexibility for integration of heterogeneous/homogeneous information resources • Providing abundant resources for knowledge discovery and knowledge construction

4. Knowledge Discovery and Construction • Knowledge construction means the active process of manipulating data to arrive at abstract models of relationships among phenomena in the world that facilitate our understanding of those phenomena and, ultimately, of the world. [1] • Knowledge discovery is a nontrivial process of identifying valid, novel, useful, and understandable pattern in data. [2] • Persistent cataloging, classification, and segmentation of digital objects is the ground for finding patterns, models, and trends of large volume data. • Reference: • MacEachren, A. et al, Constructing knowledge from multivariate spatiotemporal Data: integrating geographic visualization with knowledge discovery in database methods • Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P., 1996, From data mining to knowledge discovery: An overview. In advances in Knowledge Discovery and Data Mining, pp.1-34.

5. Types of Elementary Knowledge Organization Systems • Classification Systems • Ontologies • Taxonomies • Index Languages • Thesauri and other controlled lists of keywords • Glossary • Dictionaries • Clustering Approaches • Lexical Databases • Concept Maps/Spaces • Semantic Road Maps • …

6. Why Knowledge-based Approach for Digital Library ?1 • Providing “Conceptual Infrastructure” • Mapping out the conceptual structure and providing a common language for a field • Providing classification/typology and concept definitions. Clarifying concepts by putting them into context. Thus providing orientation and serving as a reference tool for individual researchers and practitioners and thereby • Assisting with the exploration of the conceptual context of a research problem and in structuring the problem, thereby providing the conceptual basis for the design of good research, for the consistent definition of variables, and thus the cumulation of research results. • Providing the conceptual basis for the exploration of the various aspects of a program in program planning, in the identification of approaches and strategies, and in the development of evaluation criteria • Assisting users in understanding context • Assisting information providers with conceptualizing a topic and with finding the proper term • Discovery of high quality resources • Providing frameworks for information exchange and resource interoperability Dagobert Soergel, Evaluation of Knowledge Organization Systems (KOS)

7. Why Knowledge-based Approach for Digital Library ?2 • Information Storage & Retrieval • Information system(s) in which the vocabulary is to be used • Use of the vocabulary • Vocabulary control in indexing and searching (controlled vocabulary) • Vocabulary control only for searching. Assist with clarifying a search topic and assembling all applicable concepts and terms, whether searching with a controlled vocabulary of free-text. • ISAR technique(s) (such as: printed index, computer search system). Support of inclusive (hierarchically expanded) searching • Automated vs. manual indexing or query formulation. Approach to indexing to be supported: Request-oriented vs. entity-oriented • Techniques for eliciting user needs (e.g., menu based on search tree; questions based on facet structure) • Summary evaluation of the vocabulary's adequacy for the stated purpose on the more detailed analysis as outlined below. • Translation • Language learning Dagobert Soergel, Evaluation of Knowledge Organization Systems (KOS)

8. Digital library requirements for knowledge organization schemas • The need for knowledge organization in subject gateways and discovery services, issues of application and use • Web-based directory structures as knowledge organization systems • Knowledge organization as support for web-based information retrieval, query expansion, cross-language searching • Semantic portals ECDL2000, Special Workshop on Networked Knowledge Organization Systems, http://nkos.slis.kent.edu/ECDL-NKOS-final.htm

9. Digital library requirements for knowledge based data processing • Knowledge organization for filtering, information extraction, summary • Knowledge organization support for multilingual systems, natural language processing or machine translation • Structured result display, clustering • End-user interactions with knowledge organization systems, evaluation and studies of use, knowledge bases for supportive user interfaces, visualization ECDL2000, Special Workshop on Networked Knowledge Organization Systems, http://nkos.slis.kent.edu/ECDL-NKOS-final.htm

10. Digital library requirements for knowledge structuring and management • Suitable vocabulary structures, conceptual relationships • Comparison between established library classification systems and home-grown browsing structures • Methodologies, tools and formats for the construction and maintenance of vocabularies and for mapping between terms, classes and systems • Frameworks for the analysis of assumptions and viewpoints underlying the construction and application of terminology systems • Methods for the combination and adaptation of different vocabularies ECDL2000, Special Workshop on Networked Knowledge Organization Systems, http://nkos.slis.kent.edu/ECDL-NKOS-final.htm

11. Digital library requirements for access to knowledge structures • Data exchange and description formats for knowledge organization systems, the potential and limitations of XML and RDF schemas • Handling of subject information in metadata formats • Standards and repositories for machine-readable description of networked knowledge organization schemas (as collections/systems) • Interoperability, cross-browsing and cross-searching between distributed services based on knowledge organization systems • Distributed access to knowledge organization systems: standard solutions and protocols for query and response, taxonomy servers ECDL2000, Special Workshop on Networked Knowledge Organization Systems, http://nkos.slis.kent.edu/ECDL-NKOS-final.htm

12. Discover Knowledge from Digital Archive • Geospatial information means those geo-materials that are georeferenced and having well-documented metadata • Ref. Components of a digital object in digital archive • Geospatial Content Based • Extracting knowledge by space-time-language

13. Knowledge about Space • Temporal Characteristics is embedded and could not be neglected • Acquisition • Direct Experience • Locomotion thru environment(crawling, walking, running, bicycling, driving, flying, etc.) • Stationary viewing • Secondary Environmental Experience • Static medium: maps, diagrams, paintings, photos, etc. • Dynamic medium: animate static visual figures to show changes over time • Other ways to conceive those that can not be viewed • Characteristics • Multimodal: proprioceptive, kinesthetic, auditory, visual, etc. • Language is often used to convey spatial information • Multi-perspective and scales • 充分瞭解人類獲取、整合與利用空間資訊模式，將可促進此類資訊的更有效利用，以及建立更符合實際需求的應用機制(e.g., aid for decision making)

14. Spatial Representation in GIS • Data Model • Vector: explicit • Basic elements: point, line and polygon • Raster: implicit • Geographic space is organized into partitions (layers) • Space-dominant representations focus on the spatial arrangement of entities based on the geometric and thematic properties of these entities. • Space is a neutral container • Entities only exist when associated to a layer or theme • Applied primarily in traditional mapping • Layer-based raster and vector models • Each layer is associated to a period or point in time • Change- or update-based scenario • Analysis based on similarity or dissimilarity between aggregations (layers) at different points of time

15. Why Thinking in Spatio-Tempoal ways? • Because the earth is running: It’s incomplete to describe an events/object in spatial domain only. • Learn from the past, and plan for (predict) the future. • Characteristics of Space & Time • Importance • To organize space over time

16. Discover Knowledge from Geospatial Information • Geospatial information means those geo-materials that are georeferenced and having well-documented metadata • Ref. Components of a digital object in digital archive • Geospatial Content Based • Feature Identification • Feature comparison: enhance the likelihood of relationships among features • Feature interpretation: merge the identified features and their relationships with real world entity, by domain knowledge • Linking to other resources that are related to this feature, this place and the time  parsing the collected information from metadata or lexical analysis • Demands • Link spatiotemporal data analysis techniques to GIS Feature interpretation tools must provide connections between abstract representations of data, metadata that describe those data, an analyst’s knowledge, and knowledge sources external to the data set being explored (e.g., thru digital library)

17. Feature Identification Discover Knowledge from Geospatial Information • Def: Finding instances of identifiable features in spatiotemporal data • Emphasis is on examining the distribution of data in all of its dimensions in an effort to notice any distinct object, regularity, anomaly, hot spot, etc. Example: Distribution of Tombs in Han Dynasty

18. Integrated Support for Research

19. WebGIS-based System Architecture

20. Challenges of Geospatial Information Processing • High threshold for general users • Hard to find required geospatial content/service • New retrieval technology for geospatial information • Persistent metadata and archive • Mechanism for effective management of huge volume of data set • Efficient ways for digitization/vectorization of geospatial materials • Integration with other information resources

21. Discover Knowledge by Space-Time-Language Coordinates • Constructing the linkage among diversified archives thru language (vocabulary) • Lingual coordinate has both spatial and temporal extents • Lingual-Temporal Plane: evolution of language thru time • Lingual-Spatial Plan: spatial distribution in dialect • Multi-lingual support for digital archive • Establishment of domain-specific controlled vocabulary sets, and serve as basis of ontology

22. Discover Knowledge by Space-Time-Language Coordinates Time Space Language

23. Space, Time and Language Coordinates for Digital Archives Historical GIS Time Space Digital Archives Language in Text, in Speech... Language in Time Language in Space Language Language Changes Language variations

24. Lingual Coordinate in NDAP • A lexis/vocabulary in context is analogy to the basic unit of a concept in knowledge • Lexis is the basic unit for any kind of language process, such as recognition, parsing, wordformation, semantics, conversation and analysis • Thru lexical analysis, collection of all the lexical types(詞類), lexical patterns(grammar文法), and instances could pave the base as lingual coordinate. • Collection of enough description(context incl. metadata) for a specific domain(could be a set of digital objects), ontology(collection of concepts for the domain) of that field is constructed.  How do we know if that is enough?  Need the self-learning capability in the mechanism • Atomic attributes of a place name • Name • Glyph & stroke: original writing, all the historical and contemporary writing, and Romanization(pinyin) • Pronunciation: indigenous and evolutions afterward • meaning (if we could restore to original fonts & sound) • Footprint • Could be ambiguous: M N • Time: (start, end), could be vague for historical names • Type: (geographic type, also could know the administrative level if it represents an administrative area) • Atomic attributes of a datum • People, event, time, place, object

25. Constructing Space-Time-Language Coordinates for NDAP • Geographic searching is a powerful and important tool • More than 80% information resources pertain to specific geographic areas and are either explicitly or implicitly geo-referenced. • To utilize benefits of geographic search, we have to geo-reference information contents first. • the cost of creating geographic footprints for each record (the Alexandria Digital Library Project spent $4m over four years) is very high. The automatic extraction of geo-referenced information is also possible but there is a need for sophisticated tools that go further than geographic name extraction. • Moving from information management toward knowledge management • (Demands) New ways of information search & retrieval • Traditional full-text search • Keyword-based or query by example search • Query by information content (image, audio, video, and multimedia contents) • Incorporation of geographic & temporal search • Versatile ways for presenting information & knowledge • 2D, 3D, or 4D • Multimedia, virtual reality • Map-on-demand, thru the parser of geographic names from context, or directly by the coordinates • Separation of content representation & presentation • The core is the metadata-based content analysis • CA(Information Content)Metadata Schemes for management of contents • Identify the best way of information representation and become persistent archive

26. 中國歷史文化地圖之整合應用 清代地方誌檢索 漢籍全文檢索 圖書聯合目錄查詢 人物資料庫查詢

28. Roles of Visualization in Knowledge Discovery • Role • Useful in finding holes or errors in data sets • Useful for noticing abstract features and patterns • Predigest complex relations of data sets into visual form • Facilitate access to multiple perspectives on information, thru interactivity • Facilitate decisions on appropriate model representation during analysis stage. • Process tracking: uncover key aspects of a process • Parameter control to get corresponding outcome on the fly • Functionality

29. Geolibrary • Objective: Lower the barriers for applying GIScience technologies • Approaches • Collecting and providing basic georeferenced spatial data/knowledge persistently • Building up application environment and tools for utilization of spatiotemporal knowledge and technologies • Development of spatiotemporal-based technologies for multi-disciplinary contents integration, aggregation, knowledge discovery in map-metaphor • Focus & Approach • Construction of the System Infrastructure for Spatial and Temporal Information Technology • Development of Core Technology • Establishment of Effective Service Model for Research Support

30. Clearinghouse (catalog) Metadata GEOdata Framework Standards Partnerships Clearinghouse • An instance of implementation of interoperability • Functionality • Locating the required resources/services • Maintaining a persistent catalog of resources/services for sharing • Exchange of information content • Format transformation

31. Effective Management System for Huge Volume of Data • Remote sensing data: 2TB/day;And will accumulate to 5 Peta Byte in 2005。 • According to the statistics of EU Space Center • Raw data from satellite : 100GB/day, 500GB/day (after Feb. 2002) • 800 TB data had been archived • Big Challenge of IT for cataloging, searching, retrieval, management, identification, knowledge discovery, and integration、 • Trading off between decentralization and consolidation on cost, • Convergent to multi-centers of information resources in Internet • Think about how to facilitate the collaboration among those centers – Community and virtual organization • Demands for complete architecture and services Data Grid

32. What’s the Solution • Support sharing and coordinated use of diverse resources in dynamic “virtual organizations” – Grid ! • Good technical solutions for key problems, such as • Security enhancement like authentication and authorization • Resource discovery and monitoring • Reliable remote service invocation • High-performance remote data access • -- Grid ! • Good quality reference implementation, multi-lingual support, interfaces to many systems, large user base, industrial support, etc. – Grid ! • Persistent Web Services – Grid !

33. Measuring Success • High degree of component autonomy • Low cost of infrastructure • Ease of contributing components • Ease of using components • Breadth of task complexity supported by the approach • Scalability in the number of components

34. Conclusions and Future Work • Building the right infrastructure will be crucial • Intersection of spatiotemporal coordinates and lingual coordinate constitutes a good framework both for knowledge extraction and interoperability • Consensus gathering and technology development still the major challenges for interoperability • Open System, Open Standard, and Open Source