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Journal of Cultural Heritage 14 (2013) 181–189

Available online at

www.sciencedirect.com

riginal article

emantic enhanced WebGIS approach to visualize Chinese historicalatural hazards

haochun Donga,∗, Xiaoqi Wangb, Hongwei Yina, Shijin Xua, Ronghan Xua

School of Earth Science and Engineering, Nanjing University, 210093 Nanjing, PR ChinaDepartment of History, School of Earth Science and Engineering, Nanjing University, 210093 Nanjing, PR China

a r t i c l e i n f o

rticle history:eceived 29 December 2011ccepted 25 June 2012vailable online 24 July 2012

eywords:atural hazardhinese ancient literature

a b s t r a c t

Among China’s vast majority of ancient literature, a wide variety of historical material about naturalhazards and natural phenomena are recorded. These records provide significant data and documents forresearch on historical natural hazards. However, Chinese ancient literature is heterogeneous in syntactic,structural and semantic levels, lacking systematical and scientific information collation, which hindertheir use in the research on historical natural hazards. This article presents a solution for promotingcomprehensive in-depth understanding of historical natural hazard records by developing a semanticenhanced WebGIS platform. It includes: (1) a geodatabase to systematically store and manage Chinese

emantic translationntologyebGIS

eodatabase

historical information on natural hazards collated from ancient literature; (2) an ontology to mitigatesemantic heterogeneity problems among different datasets; (3) WebGIS tools to visualize and analyzenatural hazards in a multidisciplinary way. The platform is compliant to other historical and culture data atspatial and temporal levels. A survey on users’ expectation and satisfactions are conducted. Conclusionsand discussions are also raised to suggest further improvements for the semantic enhanced WebGISplatform.

. Research aims

Among China’s vast amount of ancient literature over thousandsf years, a wide variety of historical material and data about naturalazards and natural phenomena are recorded, including floods,

andslides, earthquakes, eclipses, droughts, sandstorms, volcanoes,sunamis, wildfires, etc. It is widely recognized that historicalatural hazard research can be helpful in hazard investigationnd zonation as well as in estimating, managing and mitigatingazards on a regional or global scale [1,2]. Researchers fromarious disciplines, such as history, geography, geology and globalhange, show great interest in historical natural hazard research.n addition, the general public is also interested in understandingegional and global natural histories.

The aim of this paper is to present a solution that recoversnformation about China’s historical natural hazards from textualncient literature to their natural environments through a friendly,

omprehensive but easy-to-understand way that is aided by visu-lization, hence facilitates in-depth understanding of historicalatural hazards. We propose to collate information on Chinese

∗ Corresponding author. Tel.: +86 25 83594664; fax: +86 25 83686016.E-mail addresses: dsc@nju.edu.cn, adreacn@hotmail.com (S. Dong),

angxq@nju.edu.cn (X. Wang), hwyin@nju.edu.cn (H. Yin), xusj@nju.edu.cn (S. Xu),uronghan@gmail.com (R. Xu).

296-2074/$ – see front matter © 2012 Elsevier Masson SAS. All rights reserved.ttp://dx.doi.org/10.1016/j.culher.2012.06.009

© 2012 Elsevier Masson SAS. All rights reserved.

historical natural hazards from ancient literature into a spa-tiotemporal geodatabase and develop an ontology-based WebGISplatform. We attempt to maximize both the platform’s accessi-bility and adaptability, allowing both professionals who wouldperform in-depth historical research and the general public whoare interested in historical data to access the information easily.

2. Introduction

Conducting historical natural hazard research from ancient Chi-nese writings is not easy. It is not only because ancient Chineseliterature was written in classical Chinese, which is different fromcontemporary Chinese language, but it is also due to the factthat each natural hazard is a complex phenomenon and con-trolled by interactions of meteorological, geological, environmentaland human factors [1]. Comprehensive, in-depth understandingof historical natural hazards requires combining cross-disciplinaryfactors and analysis of historical data over a range of tempo-ral and spatial scales. Though more and more ancient archivesare digitalized and can be read online with full-text or keywordsearch capabilities, they lack systematic collation for scientific use.

This creates great barriers for further understanding and does notaddress a broader audience that includes both professionals and thegeneral public. Extracting, organizing and interpreting data fromancient archival remain problematic in the following aspects:

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and spatial (location) attributes are very important in understand-ing space distribution and time frequency of a particular naturalphenomenon, which is essential in analysis of disaster patterns, and

82 S. Dong et al. / Journal of Cul

firstly, historical literature offer a wealth of information aboutwhen (time), where (location) and how (magnitude, durationand effects, etc.) a natural hazard happened. These three “W” areimportant in the analysis of natural hazards’ spatial distributionand occurrence frequency. However, ancient documents werecompiled according to various criteria. Due to different purposes,diverse reporting styles and presentations introduced hetero-geneity in both syntactic and structural levels, which presentsdifficulties in comparative statistical analysis to show recurrencepattern as well as flexible visualization by computer systems.Hence, a logical collating process needs to be developed so thatthe maximum amount of natural hazard information can beextracted from a vast variety of ancient material and transformedinto a standard format in order to store, manage, share, integrateand visualize for in-depth understanding;secondly, names of natural events were diverse in different his-torical time and places. Ancient authors described natural eventsand their occurrences in many different ways. For example,sandstorms were recorded using a variety of names in ancientwritings, such as haze, yellow fog, rain and dust, rainfall with yel-low sand and black fog. This diversity may result from the fact thatthe ancient Chinese lacked unified scientific standards to namenatural phenomena, which resulted in the use of different termi-nology to describe the same natural phenomena. This led to manysynonymous and homonymous terms in ancient literature, whichraise semantic heterogeneity problems in information interpre-tation and integration. If one author’s terminology differs fromanother’s, keyword-based search or full-text search would havelow recalls, which suggests that not all relevant informationsources would be discovered [3]. Therefore, it is necessary toestablish a translation mechanism on a semantic level, otherwisevariable density of records about a specific phenomenon couldimpede on information discovery, retrieval, interpretation andintegration [3], which significantly impacts on statistical analysisresults [1];thirdly, it is of both theoretical and practical interests to investi-gate not only what natural hazards occurred in history, but alsowhy they happened. However, the answer to this question cannotbe found in any form of textual information, including the digi-tal format. To perform in-depth historical hazard research, datashould be combined with cross-disciplinary information in orderto produce a comprehensive analysis. Although digitalization ofancient literature makes historical records more accessible, theystill need to be recovered from textual forms and translatedinto their natural environments. Comprehensive in-depth inter-pretative analysis of historical natural hazards would be moremeaningful and effective through the integration of multiple nat-ural and social environmental factors [1].

Fortunately, advanced information technologies have providedew approaches and insights to systematically collate, manage,

ntegrate, visualize and comprehensively analyze heterogeneousistorical data in syntactic, structural and semantic levels. Forxample, the considerable development of ontology and Web-ased Geographic Information System (WebGIS), which allow forublish, integrate, analysis and visualization of geospatial datahrough the Internet [4], seem to shed new lights on solving theforementioned problems.

Ontology, originally from philosophy and later introduced intoomputer science, is defined as an explicit formal specification of

shared conceptualization [5,6]. It plays a central role in seman-ic heterogeneities and leads to semantic integration of data [7,8].

t can be used for identification and association of semanticallyorresponding concepts by providing controlled vocabularies withormal and explicit descriptions of pertinent terminologies andlassification schemes [8–10]. A good example of this is Getty’s

eritage 14 (2013) 181–189

Thesaurus of Geographic Names, which provides a structuredvocabulary intended to provide terminology about places impor-tant to various disciplines, specialized in art, architecture andmaterial culture1. Many more examples from geology, hydrology,geography and other domains have also proved that the use ofontology can effectively overcome semantic heterogeneities andfacilitate semantic query, retrieval, integration and interpreta-tion. For example, Klien et al. (2006) presented a practical use ofextent ontology-based service to overcome semantic heterogeneitycaused by synonyms and homonyms in disaster management [10].Fallahi et al. (2008) developed a layer-based ontology to discovergeo-services that support semantic interoperability in environ-mental modeling for describing and research on how the naturalenvironmental changes [11]. Tripathi et al. (2008) discussed amethodology to extend an existing ontology for earth and environ-ment to ensure interdisciplinary knowledge reuse, managementand discovery [12]. Moreover, Zhao et al. (2009) defined a set ofontology to represent domain knowledge and achieved effectivediscovery, automation and integration service of geospatial data[13].

Another technology, WebGIS has powerful capabilities to man-age, analyze and visualize diverse historical data sources. As avery popular technological tool used in examining natural haz-ards and producing hazard maps all over the world, WebGISoffers an effective support for solving problems related to geo-morphological processes based on historical data. Many WebGISapplications in fields of historical and cultural geography, archae-ology and cultural resources management in the past decades havebeen reported in literature as a beneficial tool in research. Forexample, Meyer et al. (2007) developed a simple and accessiblesystem to mange and visualize archaeological sites and monu-ments based on GIS and XML technology [14]. Lazzari et al. (2009)adopted an integrated GIS-based approach to evaluate the stateof conservation-decay of the architectural heritage and its interac-tion with natural-anthropic components [15]. Kaimaris et al. (2011)achieved systematic management of a large number of historic andcontemporary geographic data through a GIS and remote sensingintegrated approach in the research of locating buried antiquities[16]. These successful WebGIS applications for incorporating mul-tiple datasets, performing spatial analysis and providing flexibledata visualization capabilities all prove that WebGIS is a valuabletechnology in historical research.

Thus, this article presents a solution for promoting comprehen-sive in-depth understanding of historical natural hazard records bydeveloping a semantic enhanced WebGIS platform. The rest of thispaper is organized as follows. Section 3 concerns materials used inthis research. Section 4 addresses the methodology that will be usedwhen building the platform and Section 5 describes the results ofour platform. Section 6 demonstrates an application scenario basedon the platform. Section 7 presents a survey and Section 8 comesto a conclusion and raises a discussion of our current research andin what aspects that future work would concern.

3. Materials

3.1. Historical natural hazard data

Every natural hazard can be described in three dimensions: time,location and effect. Among these three aspects, the temporal (time)

1 Getty’s Thesaurus of Geographic Names, http://www.getty.edu/research/tools/vocabularies/tgn/.

S. Dong et al. / Journal of Cultural H

Table 1Table structure of China historical natural hazards.

Fields Field type demo

Hazard ID Int Primary keyHazard name nvarchar(50)Time Time Format (mm-yyyy)Location nvarchar(50) Foreign keyOriginal source nvarchar(255) Foreign key

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resolution satellite map of China are both used as base maps. Theyare transformed into vector and raster layers superimposed in aWebGIS-based platform. The former represents the distribution of

Original description Text Original description quotedfrom ancient literature

ould aid disaster mitigation and reduction. The effects of naturalazards which include magnitude, duration, scope of the impactnd other related information will improve analysis of hazard con-equences and influences.

Historical natural hazard data used in this paper are obtainedrom Chronicle of Great Natural Disasters and Abnormal Phenom-na in Ancient China, one of the most comprehensive books fundedy National Natural Science Foundation of China. It collates his-orical natural hazards recorded from a variety of China ancientocuments (including local chronicle, Twenty-Four Histories, ancientydraulics, Miscellanies etc.) dating from around 200 B.C. to 1911 A.. [17].

In order to maintain as much information as possible at a stan-ard quality so that historical records from different time periodsnd sources can be integrated and compared, a relational tableTable 1) has been designed to format historical natural hazardata for storage and management. The table contains the followingelds:

the “Hazard ID” field is the primary key of the table for the pur-pose of unique identification;The “Hazard name” field keeps what ancient authors recordedeach hazard event or phenomenon in historical literature as. Itmight differ from its contemporary name. The original hazardname was kept and would be semantically translated in the nextsection for retrieval and integration purposes;many historical literatures contain important descriptions ofwhere and when natural events happened, which could be trans-ferred to WebGIS for spatiotemporal analysis. So two fields havebeen designed specifically to store spatial and temporal informa-tion respectively in Table 1. These two fields would be geo-linkedto geological or geographical maps so that historical natural haz-ard records could be plotted on a map and enable spatiotemporalpattern analysis;the “Original source” and “Original description” fields are quoteddirectly from ancient literature that indicates which sourcesrecorded this event and how it was described. These two fieldsare used to keep connections between records and their origi-nal ancient literature. The connections would help users to trackback to their original copies if users have further interests to readthrough.

Information is extracted systematically from the book Chroniclef Great Natural Disasters and Abnormal Phenomena in Ancient Chinand transformed into Table 2. From this table, we can browse andetrieve detailed information about every natural hazard event in aextual format. Meanwhile, once it is geo-linked to a geological oreographical map, the occurrence frequency of every type of haz-rd during a historical time span can be easily analyzed statistically.tatistical data superimposed on geological maps would displayhe spatial distribution of each hazard and help further analysis of

he trigger factors in addition to improving the process of iden-ifying correlation between different natural hazards and naturalnvironments.

eritage 14 (2013) 181–189 183

3.2. Ontology

As there are many different terminologies and different classi-fication schemes used to name or describe natural phenomena inancient Chinese literature, which inevitably introduces a semanticheterogeneity problem in data integration and sharing. This createsa barrier for in-depth analysis and statistics by computer systems.Unfortunately, traditional information searching methods cannotextract implicit meaning and relationships among different termsin datasets. In this paper, an ontological approach is adopted toprovide a controlled vocabulary with formal descriptions of thepertinent concepts, which acts like a bridge between ancient liter-ature and source data to reconcile semantic heterogeneities amongdifferent ancient literature.

A collation of different kinds of terminologies in ancient Chineseliterature is made and their corresponding terms in contemporarynatural hazard researches are used to construct a natural hazardontology. The natural hazard ontology can be simply described asa tree (Fig. 1a). O1, O2,. . ., On represent different terms, alias, orsynonyms used in ancient Chinese literature to describe a partic-ular natural hazard. O represents the natural hazard ontology. Thearrow represents an “is a” relation which means every On is onekind of O. Using sandstorm as an example, we construct a classnamed sandstorm, a term commonly called today. Rain and dustis a phenomenon that was equivalent to sandstorm in ancient lit-erature. Thus a subclass named “rain and dust” is constructed andan equivalent relationship between the class of sandstorm and thesubclass of rain and dust are also established (Fig. 1b). Once thesubclasses are mapped to the datasets (Fig. 1c), relationships areestablished between ancient hazard names in datasets and con-temporary vocabularies that are equivalent in meaning.

The ontology is coded in OWL2, which provides an organiza-tional structure for classifying data that can be discovered by bothhuman beings and computer systems. The following is a fragmentof natural hazard ontology used in this study, in which a class sand-storm is defined:<rdf:RDF>. . .. . .//define class<owl: Class rdf: ID=”Sandstorm”/>”. . .. . .<rdfs:subClassOf rdf:resource=”# haze”/>. . .. . .<rdfs:subClassOf rdf:resource=”# yellow fog”/>. . .. . .<rdfs:subClassOf rdf:resource=”# rain and dust”/>. . .. . .<rdfs:subClassOf rdf:resource=”# black fog”/>. . .. . .<rdfs:subClassOf rdf:resource=”# rainfall with yellow sand”/>. . .</owl>. . .. . .</rdf:RDF>

3.3. Geological/geographical data

It is difficult to find a place in China that has no records ofoccurrences of natural hazards, and it is easy to find some placesranking higher than others in the frequency of a certain naturalhazards due to the fact that natural hazards are closely pertinent tonatural environments. Therefore, in addition to historical recordsstored in a relational table, local natural environmental datasetsthat include lithology, structures, geomorphologies, hydrologicalconditions, vegetation and climate data, should be considered forcomprehensive historical natural hazard research.

In this study, a 1: 500,000 geological map and a 1000 m-

2 OWL, Ontology Web Language, http://www.w3.org/TR/owl-features/.

184 S. Dong et al. / Journal of Cultural Heritage 14 (2013) 181–189

Table 2Example records in the table of China historical natural hazards.

Hazard ID Hazard name Time Location Original source Originaldescription

. . . . . . . . . . . . . . . . . .

2 (Wind and fog) 02-1523(Feb, 1523)

(Shandong Province) (Jiajing Reign, Note ofQinzhoufu, Vol. 5)

(In February, strong windmade the sky dark duringthe daytime. People cannotsee the road)

3 (Wind and fog) 1523(1523)

(Shandong Province) (Kangxi Reign, Note ofDongming County, Vol. 7)

(Strong wind, dark duringdaytime. . .)

4 (Wind and fog) 12-1534(Dec, 1534)

(Shandong Province) (Qianlong Reign, Note ofDongming County, Vol. 7)

(In December, strong wind,dark in the day time. . .)

. . . . . . . . . . . . . . . . . .

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ifferent types of rocks and surficial deposits, as well as the loca-ions of geologic structures such as faults and folds3, while the latterrovides a general survey of the area where historical natural haz-rds occur. The combination of the geological map and satelliteap provide adequate background information that help answer

uestions such as: where are some certain types of hazard likelyo occur; what scientific principles govern the processes responsi-le for the hazard and how subsurface distribution of porous and

mpermeable rocks affect the flow of heavy rainstorms.

. Methodology

A browser/server architecture based on ArcGIServer + Microsoft Visual Studio .NET framework is adopted touild the entire platform with the aim to provide a user-friendly

nterface for data viewing and retrieval to users.

3 Geological map, http://geoinfo.nmt.edu/publications/maps/geologic/whatis.tml.

mantic mapping.

The platform is implemented in a four-layer architecture thatfollows service oriented architecture (SOA) principles as illustratedin Fig. 2. Each layer has distinctive functions and provides interfaceto the layer above, which makes the whole system able to supporta wide range of functions and has the extensible ability to imple-ment new ones. This architecture allows remote users interact withthe system, exploiting historical data of their interests and issuingqueries to retrieve information they need without extensive train-ings in using the system. The platform is also compliant to otherhistorical GIS developments and applications, which allows easydissemination and visualization, flexible retrieval and analysis ofhistorical culture data.

4.1. Data layer

In the data layer, ArcGIS geodatabase is used for storage, man-agement and integration of multi-source datasets. It combines“geo” (spatial data) with “database” (data repository) to create a

S. Dong et al. / Journal of Cultural Heritage 14 (2013) 181–189 185

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entral data repository for spatial data storage and management4.atasets, including historical datasets, geological maps and satelliteaps, etc., are stored in attribute, vector (points, lines, polygons)

nd raster types. They are represented as multiple layers superim-osed together or joined in GIS-based tools for browsing, retrievalnd spatial analysis in the application layer.

.2. Semantic layer

The second layer is the semantic layer. It consists of ontologiesnd mapping mechanisms for semantic translation and data map-ing, which will help to mitigate semantic heterogeneity problemsnd make query, integration and statistics possible and accurate.ore specifically, ancient terminologies could be translated into

niformed expressions when analyzed, whereas contemporaryocabularies could be translated into ancient terminologies whenetrieved. This makes it possible for different users to access to theistorical natural hazard records in a uniform fashion no matterhat different terminologies were used in the past.

.3. Service layer

The third layer is the service layer which implements GISunctionalities and Web services. ArcGIS server is adopted toevelop Web-based GIS system in this research. It is responsibleor introducing advanced GIS functions to the Internet and to geo-isualization resources managed in the geodatabase. It is used forntering and handling historical data in response to the need forapid access to databases and to represent data that references the

osition of natural phenomena. The Web Server is used to deployeb services and host Web applications running in the GIS server.

4 Geodatabas, http://www.esri.com/software/arcgis/geodatabase/index.html.

-based GIS platform.

4.4. Application layer

The top layer is the application layer, which serves users overInternet or via LAN. Users can simply use Internet explorer tobrowse, retrieve, locate data and represent spatial analysis results.Detailed functions and applications for different user scenarioswould be addressed in the next section.

5. Results

Based on the above platform architectural design and imple-mentation, a system has been developed that can not only integratevarious historical natural hazards recorded in diverse ancient liter-ature, but also provide a well-designed graphical user interface toaccess the database and represent data in an enhanced interpreta-tive and visualizing way. Users can connect to the platform simplyusing a Web browser and accomplish the following functions in aneasy-to-use way.

5.1. Information browsing: viewing China’s historical naturalhazards both in a conventional HTML mode and a map navigationmode

This function gives users the ability to switch between twobrowsing environments to view historical natural hazard informa-tion: the textual and map environment. In the textual environment,all historical natural hazard data is represented in a table, sorted bytype, time and place in a hierarchical tree structure on the left sideof the page (Fig. 3). Users can select one natural hazard event tonavigate through detailed information that is extracted from thegeodatabase dynamically.

Clicking on the map navigation button would lead users to

switch to a map visualizing navigation environment from the tex-tual one, which would enable users to browse natural hazardsaccording to their geographical locations on a map (Fig. 4). In thismode, users can manipulate maps with universal GIS tools such as

186 S. Dong et al. / Journal of Cultural Heritage 14 (2013) 181–189

Fig. 3. An example of textual information browsing mode.

Fig. 4. An example of map navigation mode.

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S. Dong et al. / Journal of Cul

review, pan, zoom in/out throughout the map server, identify fea-ures on the map and control different map layers display or hide.atural hazard events would be plotted on a map so that it is easy

o navigate the spatial distribution.

.2. Data retrieval: search for relevant data by semanticranslation

It is a semantic enhanced search function that facilitates userso discover detailed historical natural hazard events on a map withextual contexts through time and space. Simple queries by key-ords: time (in solar calendar or Chinese ancient dynasties), place

nd type of events or combination of keywords for several char-cteristics are possible. The search requests would be semanticallyranslated into vocabularies that were used in history and mappedo targeted records in the geodatabase so that users can seamlesslyearch across different terminologies without exclusion of relevantnformation.

In the map visualizing navigation mode, users are able to searchor detailed hazard information by drawing a rectangle on the mapo explore which natural hazards in history occurred within thepecified spatial scope indicated by the rectangle on the map. Usersre also able to search for spatial distribution of natural hazards bypecifying a hazard type as an input parameter.

.3. Data exploration: discover damage frequency andistribution of phenomena by using map navigation

Users can utilize this function to produce interpretable andnformative thematic maps by symbolizing aggregated data. Theommon forms of aggregated symbols for representing numericalata on maps are graduated circles, density dots, stacked bars, pro-ortional columns in which the area of the circle, the mass of the dotr the height of the column are scaled in proportion according toata values. This function enables users to get a full understandingf the spatiotemporal distribution of any type of natural hazardsor the specified time span.

These thematic representations would facilitate the followingpatial analysis, but not limited to:

examining occurrence frequency of a certain natural hazard ininterested areas or interested time span;producing historical hazard zonation maps based on spatial dis-tributions;comparing correlations of multiple phenomena occurrences;identifying areas where events occur repeatedly or with greatintensity.

Using plague and drought as examples, Fig. 4 shows the spatialistribution correlation of these two hazards. In this thematic map,he area of the dot indicates the frequency of plagues (from 1423.D. to 1904 A.D.). The larger the dot, the more frequently plaguesccurred. The gradient color indicates the frequency of droughtsfrom 394 A.D. to 1901 A.D.). The darker the color, the more oftenroughts occurred. These two hazards show a positive correlation

n spatial scales.

. Experimental applications

In this section, a user scenario will be illustrated to demonstratepplications of this platform.

A middle school student, Kevin, is interested in if China hasad severe sandstorms in the past. He does not know what sand-torm was named in ancient China. He types a keyword “sandstorm”nto the query textbox and constrains the time span from 1200 to

eritage 14 (2013) 181–189 187

1900 A.D., but there are not any results returned by the conven-tional searching method, because there is no explicit use of theword “sandstorm” in the natural hazard geodatabase, and the searchis unable to infer the inner relationship between sandstorm andequivalent ancient terminology. However, in our platform, whenthe Web server receives a request for “sandstorm”, the system gen-erates a query against the ontology, and sends the query to themapping illustrated in Fig. 1c. The mapping will deconstruct thequery into several sub-queries, such as haze, yellow fog, rain anddust, rainfall with yellow sand, black fog, and sends each of them totheir targeted terms in the geodatabase. Kevin is then providedwith the illusion of using the same vocabulary as ancient Chi-nese documentation, bridging disparities between modern Chineseand ancient Chinese terminology. All different ancient terminolo-gies that are mapped to “sandstorm” are clustered and counted asthe same natural phenomenon. After the semantic translation andsearch process, Kevin would receive hundreds of records matchinghis search request.

In addition, Kevin wants to perform an analysis to identify wheresandstorm occur repeatedly or with great intensity in history. Thisanalysis could not be accomplished without the accurate searchresults from the previous step. With China’s provincial map as abase map, he would clearly see that ancient sandstorms occurredwith a high frequency in the north part of China, a low-temperaturezone that is arid, less vegetated and has low level of precipitation, allof which are necessary conditions to form sandstorms. Conversely,sandstorms could cause substantial drops in temperature that leadto heavy snow, frozen soils and nutrition loss in the region thatreduce the agricultural productivity and influence local inhabitants’normal lifestyles [18,19]. If this information is combined with his-torical facts, Kevin can comprehend historical events even further.For instance, Kevin would be able to learn that northern China wasthe ideal homeland for nomadic people in ancient China, but thisabominable weather and environment once increased the fatalityof both people and livestock, therefore it caused nomadic peopleto invade the Han nationality that lived in less northern parts onseveral occasions for a better living environment [20]. This cross-disciplinary explanation deepens Kevin’s understanding of historyand may also further his interests in natural history.

In the next application scenario, Kevin drags his mouse on themap and places it over the northeast part of China. He finds aplace indexed in the UNESCO World Heritage list called Wudalianchiwhere the search results indicate that many volcanoes erupted inhistory. Examining the historical volcano distribution map, Kevincan see very clearly that historical volcanic eruptions are denselydistributed in Heilongjiang and Jilin provinces, Northeastern China.These areas are economic development regions in agriculture,forestry and tourism. This then brings up the question of “Whyare volcanoes more conductive to take place in these areas than otherplaces in China?”. Using geological maps as base maps, Kevin canunderstand that these areas are situated along converging plateboundaries where subduction occurs, which is one of the princi-pal geological settings for volcanism. The process of volcanismsmolds these areas into spectacular landforms that are now knownas World Geological Parks, attracting a large amount of world-wide tourists every year. After volcanoes erupted, large amountsof volcanic ashes were discharged and reactions with water andatmospheric gases occurred, forming very fertile soil that sup-ported lush vegetation and crops. This made Northeastern Chinaone of the major grain producer in China. However, these erup-tions also represented significant disasters, including destructionof crops, buildings, transportation and communication systems in

addition to pollution of water supplies. Moreover, forests and allliving creatures within a distance of 10 km from the volcanoeswould have been destroyed and killed. This implies that even nowa-days, they are still high-risk volcanoes because over 100,000 people

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88 S. Dong et al. / Journal of Cul

ive near them. With the addition of the above mentioned back-round information, Kevin can obtain a better understanding ofhe natural history of Northeastern China, particularly in the field ofolcanic-related hazards, which compliments his knowledge of theightseeing of the area. The user journey in this platform presentso Kevin an innovative way to read history and comprehensivelynderstand historical events.

. Evaluation

A concise survey had been conducted to assess users’ satis-action and expectation on the platform, and allow users to offeruggestions for modifications and further improvements. Fifty-sixnonymous users participated in this survey and gave positive feed-ack on the system (Table 3). Ninety-three percent of participants

ndicated that the system is interesting, 86% indicated that the sys-em is meaningful, and 84% believed that the system can promotend deepen historical natural hazard research. Moreover, the sur-ey tells us that the cross-disciplinary perspectives on analyzingistorical natural hazards through visualized presentation is theost popular and attractive functions for users, whereas semantic

earch and information browsing are ranked second and third. Inddition to these statistics, survey participants also give valuableuggestions, which are concluded as follows:

some users suggest to develop new functions to support updatedinformation not only by system developers from the server side,but also to provide access to insert or modify data or add com-

ments at the client side by general users, like Wikipedia, Facebookand other websites. This allows users to become more engagedand positively interactive with the system rather than limit usersto reading the contents from a screen at a distance;

able 3eedbacks from survey users.

Questions

Do you think this system is interesting?Very interesting ©5

©4©3

©2

Not interesting at all ©1

Do you think this system makes historical natural hazard research meaningful?Very meaningful ©5

©4

©3

©2

Not meaningful at all ©1

Do you think this system can help you understand historical natural hazard in a new wYes ©5

©4

©3

©2

No at all ©1

Do you think this system can promote historical natural hazard research deeper and mYes ©5

©4

©3

©2

No at all ©1

What function(s)/information do you expect most from the system?Information browsing: viewing China historical natural hazards both in a conventional

Data retrieval: search for interested data by semantic translation

Data exploring: discover phenomena damage frequency and distribution by using ma

Integrate geological, geographical and environmental factors to analysis and provide

eritage 14 (2013) 181–189

• besides the descriptive information relating to each historicalnatural hazard, users also want to learn about the latest researchconducted in specific districts or areas. So it could be more mean-ingful to make links to the latest literature, reports or media newsrelated to each historical natural hazard founded in the database;

• in order to make this system more accessible and convenient,users suggest developing a mobile version so that they could visitit through mobile phone or iPad any time any place. Once thesystem performs a data update, the system would post updateannouncements through social networking sites such as Twitter,Weibo (a Chinese Web service that functions in a similar way toTwitter), or Facebook so that targeted users would be notifiedautomatically;

• linking or integrating historical natural hazard information out-side of China could also strengthen the system. This may helpraise potential international research cooperation at a global scaleand provide a wider perspective in global change.

8. Conclusions and discussion

The goal of this article is to present an example of building aplatform to store, manage, represent, inquire and analyze historicalnatural hazard records in a flexible, convenient and interpretativeway. To do this, a semantic enhanced WebGIS platform has beendeveloped which combines:

• a geodatabase to provide spatiotemporal data storage and man-agement;

• a domain ontology to mitigate semantic heterogeneity problems;• WebGIS tools to offer cross-disciplinary perspectives to arouse

interests and inform people of not only what happened in historybut also why it happened.

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flexible data visualization 82

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The experiments that we have done in this paper show that:

the geodatabase is flexible to store and manage diverse hetero-geneous datasets, including attribute data, vector data and rasterdata. It provides a central data repository for easy data entryand user access in the field of historical natural hazard research.It would be improved by extracting more individual traits ofdifferent natural hazards for richer representations and furtherpractices in the geodatabase world;ontology-based semantic integration is promising for scientificdata integration and navigation. Construction of natural hazardontology and development of semantic mapping methodologyenable us to identify and retrieve information among ancient lit-erature. It mitigates semantic gaps between ancient literatureand common language used today, makes semantic search pos-sible and helps to improve searching accuracy. The developmentof ontology is an iterative process, it needs to be updated andimproved when more ancient terminologies are systematicallycollated;the WebGIS-based platform presented in the paper providesconventional and advanced functionalities for visualizing andanalyzing historical natural hazards distributed in spatiotem-poral scales. It allows different users to utilize historical datafor multiple purposes. The proposed platform is compliant andsupports not only historical data but also modern data. It also sup-ports natural hazard data as well as data from other disciplines.The novel design of the platform makes dynamically insertingnew data very easy.

Current application cases and feedback affirm that this platforms effective and meaningful. They also suggest further directions forterative modifications and improvements. Integration of diversityf environmental factors, mapping mechanisms and highly visual-zed data representation modes should be consistently updated inrder to adopt more complex requirements. Evaluation and ques-ionnaires on users’ expectation and feedback would be conductedontinuously to increase familiarity with targeted audiences.

As a historical research approach, we believe that it is neces-ary to develop innovative functions to facilitate in-depth studiesf extraordinary cultural and historic resources recorded in ancientiterature such as the one we have hereby presented as constantenewal is the best way of preservation [21].

cknowledgements

This research has been supported by National Natural Science

oundation of China (Project No. 40802080), Jiangsu Plannedrojects for Postdoctoral Research Funds (Project No. 0206003405)nd Humanities Fund of Nanjing University. Authors would likeo appreciate American Association of Museum and Professor

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eritage 14 (2013) 181–189 189

Christina Hsu from Taiwan for their continuous supports increative thinking, constructive suggestions and encouragements.Careful reviews from two anonymous reviewers are also greatlyappreciated. Thanks also go to Miss Anna Mo Zhou from TuftsUniversity for proofreading the whole paper.

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