Life Science Dictionary:
A Versatile Electronic Database of Medical and Biological Terms

Shuji KANEKO
Graduate School of
Pharmaceutical Sciences
Kyoto University
skaneko@pharm.kyoto-u.ac.jp

Nobuyuki FUJITA

Yoshihiro UGAWA

Takeshi KAWAMOTO

National Institute of
Genetics
nfujita@lab.nig.ac.jp

Miyagi University of Education Hiroshima University Graduate
School of Biomedical Sciences
ugawa@ipc.miyakyo-u.ac.jp
tkawamoto@hiroshima-u.ac.jp

Hiroaki TAKEUCHI

Masataka TAKEKOSHI

Hiroshi OHTAKE

Shizuoka University

Tokai University School of
Kyoto Prefectural University of
Medicine
Medicine
sbhtake@ipc.shizuoka.ac.jp mtakekos@is.icc.u-tokai.ac.jp ohtake@koto.kpu-m.ac.jp

Abstract
In parallel with the recent progress in life sciences, vast numbers of words for new substances and phenomena have been appearing. Since 1993, we have been analyzing English texts of medical journals selected mainly
from the public MEDLINE database and collecting frequently-used terms together with their frequencies, concordances, typical usages, definitions and translations. The data were recorded in a versatile relational databaseand edited into several text-based, English-Japanese and Japanese-English dictionaries intended for public release. We have also developed convenient online and offline systems for our electronic dictionaries and areproviding them on our homepage (http://lsd.pharm.kyoto-u.ac.jp/). The recent 2003 version of the online dictionary WebLSD contains 39,790 entries of English terms with their translations and definitions, 26,000 example sentences for 5,100 words, and 938,000 records of concordances for 9,500 words. The access log statisticsof the WebLSD server indicate more than 20,000 searches per day, and the number has been increasing exponentially year by year. We are recording the English pronunciations of 5,000 terms using multiple scientists'voices, and the test version of the WebLSD voice was released recently. Since our database can be extended toany language, we are planning to collect Chinese translations of life science terms, with the aim of creating a
multi-language life science dictionary that includes English, Japanese and Chinese.

1Introduction‘Life Science’ is a modern academic field that mainly consists of genome-based, molecular and systemic
studies on living organisms (i.e. biology), including humans (i.e. medical sciences). Current progress in thisfield has resulted in vast numbers of research reports describing the findings of new substances or phenomena.
Most of these reports are written in English, the practically ‘standard’ language in natural sciences, so thatJapanese scientists and students have to understand the meaning of new terms and translate them into Japanesefor domestic communications. As for the standardization of Japanese scientific terms, there are several thesauri
made by governmental institutions. There are also many medical and biological dictionaries in printed format.
However, the revision cycles of these publications generally take several years, which are too long for followup of new terms. Moreover, there is no information on usage or collocation for the proper use of original English terms in the previous scientific dictionaries and thesauri. Such an unsatisfactory situation prompted us toproduce a novel dictionary system truly useful for Japanese scientists and students studying life science.

12Life Science Dictionary

Our dictionary is not a simple collection of scientific terms but a flexible database aimed at creating newelectronic knowledge-base services. The following sections describe how our system has been constructed.

2.1Collection of life science terms

In medical sciences, most of the bibliographic citations and author abstracts from more than 4,600 biomedical journals have been accumulated in the MEDLINE database since mid-1960s by the National Library ofMedicine, USA. Also, titles and abstracts from biological journals have been compiled into BIOSIS database,which is available from several online distributors. Since most of the scientific terms and concepts have beenoriginated from English literature, we first analyzed the frequency of words appearing in English titles and abstracts that were selected from Current Contents Life Science, a quick report version of MEDLINE andBIOSIS databases. By analyzing 1-Gbyte text (12 million words) with our original Perl script, we found thatthe corpus of 3-year reports consisted of 220,000 types of words and that the number of words vs. frequency
level showed an inversely proportional pattern in a logarithmic plot (Fig. 1 left). Detailed inspection of theranked words revealed that most of the low-frequency words (once or twice in 3 years) were misspellings orparticular abbreviations that should not be translated. Furthermore, only 46,270 words of a frequency level ofmore than 5, corresponding to 21% of the overall types, are required to cover 97.4% of the total 1-Gbyte text
(Fig. 1 right), suggesting that a vocabulary of 50,000 words is basically enough for the understanding of current life science literature, which was set as the tentative target scale of our dictionary.
In 1998, the MEDLINE database was opened for public use as free PubMed. Since then, we have periodically analyzed English text from PubMed and collected the differential population of words that involves
newly appearing terms (about 2,000 words per year). We have also analyzed several Japanese texts offered bycollaborating medical publishers to collect Japanese terms. As of May 2003, approximately 140,000 English
and 50,000 Japanese terms have been gathered with their statistical data from multiple sources. Since proper
usage of a particular word can be judged by example sentences and concordance, we selected frequentlyoccurring words and collected 26,000 example sentences for 5,100 words, and 938,000 concordance records
for 9,500 words in keyword-in-context (KWIC) format (see below).

Figure 1: (Left) Vocabulary used in life science articles. The frequency of each word was analyzed in 1-Gbyte
text of life science papers that were written by authors belonging to institutions of English-native countries
and were published in the most frequently-cited journals during 1994-1996. The horizontal axis of the graphindicates the level of frequency classified as 1, 2, 3-5, 6-10, 11-20, 21-50, and so on (plotted at underlined labels). The vertical axis indicates the types of words at the frequency level in logarithmic scale. Example
words are shown above the plot. Numbers with double-head arrows indicate the percentage of word types in
the indicated range of frequency level. (Right) Vocabulary required for the understanding of life science articles. The graph shows that the indicated percentage of total words in the literature can be covered by theword types whose frequency level are equal to or more than the corresponding level.

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2.2

Design of relational database

To compile multiple tables of data systematically, we designed a relational database that can be easily converted into text-base dictionaries (Fig. 2). In the structure, each table contains several fields of records, one ofwhich is a non-redundant set of indices used for defining a relation between different tables. Since many English terms correspond to multiple Japanese words and vice versa, there is an intermediate table of translationthat defines individual English-Japanese equivalents. Conversions from the relational data to text-base dictionaries were embedded as a function of the database. From the pairs of Kana readings and Kanji characters, aKana-Kanji conversion dictionary is made for Japanese computer users. Frequency statistics of English words
produce a spelling dictionary for word processing software. E-J and J-E dictionaries are made from the core
structure of the database, which will be extended to multimedia dictionaries by incorporating voices and video
clips in the future.

Figure 2: Structure of relational database for making multiple dictionaries. Each box indicates a separate table
whose direction of reference is shown by arrows.

2.3

Translation and annotation

The translation of words was done by us with help from many volunteer specialists, who made significant
contributions in examining the entries. In addition to the equivalent English and Japanese words, each translation record contains some flags indicating part of speech, attribution, commonly-used subfield of life science,and brief explanation, if needed. Tables 1 and 2 summarize the present 56,114 records of translation table inour database. As a collection of words in a particular field of science, two thirds of the records are nouns
mainly consisting of anatomical, chemical, taxonomical and methodological terms. Collection of abbreviationsis at a preliminary stage because of their redundancy and inconsistency.

Table 1 Translation table contents
Part of Speech
NounAdjective
Verb
AdverbAbbreviation
Latin*Others
TotalWords
37,66910,696
3,573
1,532
1,115
882647
56,114

Table 2 Attribution of nounal entries

Ratio
67%
19%
6%
3%
2%
2%
1%
100%

Attribution
Anatomical terms
Chemical names
Phenomena and functions
Materials and substances
Methods and actions
Diseases and symptoms
Endogenous substances
Conditions and states
Proper nouns
Animals and plants
Intellectual productsUnits and measures
Total* including Latinate nouns, adjectives,
adverbs and others.

3Words4,802
4,774
4,695
3,580
3,390
3,184
2,974
2,716
2,597
1,968
1,654
1,335
37,669

Ratio
13%
13%
12%
10%
9%
8%
8%
7%
7%
5%
4%
4%
100%

2.4

Public service of electric dictionary

For the convenience of stand-alone computer users, we have produced electric dictionaries and tools for
Kana-Kanji conversion, E-to-J or J-to-E lookup and an English spelling checker. All these files are available
for free at our homepage (http://lsd.pharm.kyoto-u.ac.jp/).
We have also developed online dictionary systems including a Web-based dictionary WebLSD (Fig. 3), andgloss-embedding systems, WebEtoJ and WebEtoJ_voc (see our another paper by Ohtake et al.). The recent
2003 version of the WebLSD contains 39,790 entries of English terms with their translations and definitions,
26,000 example sentences for 5,100 words, and 938,000 records of concordance records for 9,500 words. We
are planning to record the English pronunciations of 5,000 terms using multiple scientists' voices, and the firsttest version of the WebLSD voice was released recently. A special feature embedded in WebLSD enables acontribution of users to our project. If someone found a new word unregistered in WebLSD, the user can post
the word and its translation on a separate page. After validation of the posted word by our collaborators, it isregistered to our database, which will be included in the next revision of WebLSD. Through this feedback
page, we are receiving more than 200 requests per month.
Another characteristic of WebLSD is the abundant information on concordances (Fig. 4), in which a maximum of 300 examples are displayed in KWIC format. Inspection of the concordances will help Japanese scientists in writing English sentences correctly. This is the striking advantage of the online dictionary, compared toa dictionary in printed format, because there is no limitation in the size of the electric dictionary.

Figure 3 An example of online WebLSD display. A user inputs a query in the lower area with a choice of several options. The WebLSD server responds to the query by activating either of E-to-J or J-to-E cgi Perl script
depending on the character code of the query. In the output, a heading is followed by its frequency level(ranked by the number of asterisks), and links to typical usages, KWIC concordance, and voice. The second
and third lines of each record show its translation with reading and synonyms, respectively. Users can contribute to our database by posting a new word from the link button. In this example of ‘express’ appearing inlife science articles, it is mostly interpreted as a verb that indicates a transcriptional change from genome
DNA to RNA. Consequently, there are some idiomatic phrases frequently used in current molecular biology,of which brief explanations are added before the translation in the case of ‘expressed sequence tag’ and ‘expression vector’.

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Figure 4 An example of a concordance window in WebLSD. Users can choose the sorting index (actually blueon the display) from the word immediately to the left or right of the relevant word (red on the display). In thisexample, the user will understand easily that the term ‘apoptosis’ (cell death by nuclear DNA fragmentation)
can be accompanied by the verb ‘undergo’.

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Conclusion and future perspectives

The Life Science Dictionary project, founded in 1993, is a research project to develop a systematic databasefor life science terms and tools for the convenience of life scientists. Our services are designed to provide andencourage access within the scientific community to the most up-to-date and comprehensive information on
English-Japanese translation of life science terms. Users can make use of the contents of our software for personal use at minimum expense for internet access. The idea has been supported by many users, and the accesslog statistics of the WebLSD server indicate more than 20,000 searches per day, which is still increasing. Inkeeping with the users’ expectations, we would like to enrich and refine the database records along with thedevelopment of life sciences, aiming to be a core virtual knowledge-base in internet cyberspace. In addition,
we are planning to collect Chinese translations of life science terms during the next 5 years to facilitate themutual understanding among Asian scientific communities in the future.

Acknowledgment
This work has been supported by Grants-in-Aid for Publication of Scientific Research Results (1994-2001,2003) from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

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