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There's an Endless Variety of World Views, and Almost as Many Ways to Organize and Describe Them
Ontology is one of the more daunting terms for those exposed for the first time to the semantic Web. Not only is the word long and without many common antecedents, but it is also a term that has widely divergent use and understanding within the community. It can be argued that this not-so-little word is one of the barriers to mainstream understanding of the semantic Web.
The root of the term is the Greek ontos, or being or the nature of things. Literally — and in classical philosophy — ontology was used in relation to the study of the nature of being or the world, the nature of existence. Tom Gruber, among others, made the term popular in relation to computer science and artificial intelligence about 15 years ago when he defined ontology as a "formal specification of a conceptualization."
While there have been attempts to strap on more or less formal understandings or machinery around ontology, it still has very much the sense of a world view, a means of viewing and organizing and conceptualizing and defining a domain of interest. As is made clear below, I personally prefer a loose and embracing understanding of the term (consistent with Deborah McGuinness's 2003 paper, Ontologies Come of Age [1]).
There has been a resurgence of interest in ontologies of late. Two reasons have been the emergence of Web 2.0 and tagging and folksonomies, as well as the nascent emergence of the structured Web. In fact, on April 23-24 one of the noted communities of practice around ontologies, Ontolog, sponsored the Ontology Summit 2007 ,"Ontology, Taxonomy, Folksonomy: Understanding the Distinctions."
These events have sparked my preparing this guide to ontologies. I have to admit this is a somewhat intrepid endeavor given the wealth of material and diversity of opinions.
Overview and Role of Ontologies
Of course, a fancy name is not sufficient alone to warrant an interest in ontologies. There are reasons why understanding, using and manipulating ontologies can bring practical benefit:
- Depending on their degree of formalism (an important dimension), ontologies help make explicit the scope, definition, and language and meaning (semantics) of a given domain or world view
- Ontologies may provide the power to generalize about their domains
- Ontologies, if hierarchically structured in part (and not all are), can provide the power of inheritance
- Ontologies provide guidance for how to correctly "place" information in relation to other information in that domain
- Ontologies may provide the basis to reason or infer over its domain (again as a function of its formalism)
- Ontologies can provide a more effective basis for information extraction or content clustering
- Ontologies, again depending on their formalism, may be a source of structure and controlled vocabularies helpful for disambiguating context; they can inform and provide structure to the "lexicons" in particular domains
- Ontologies can provide guiding structure for browsing or discovery within a domain, and
- Ontologies can help relate and "place" other ontologies or world views in relation to one another; in other words, ontologies can organize ontologies from the most specific to the most abstract.
Both structure and formalism are dimensions for classifying ontologies, which combined are often referred to as an ontology's "expressiveness." How one describes this structure and formality differs. One recent attempt is this figure from the Ontology Summit 2007's wrap-up communique:
Note the bridging role that an ontology plays between a domain and its content. (By its nature, every ontology attempts to "define" and bound a domain.) Also note that the Summit's 50 or so participants were focused on the trade-off between semantics v. pragmatic considerations. This was a result of the ongoing attempts within the community to understand, embrace and (possibly) legitimize "less formal" Web 2.0 efforts such as tagging and the folksonomies that can result from them.
There is an M.C. Escher-like recursion of the lizard eating its tail when one observes ontologists creating an ontology to describe the ontological domain. The above diagram, which itself would be different with a slight change in Summit participation or editorship, is, of course, but one representative view of the world. Indeed, a tremendous variety of scientific and research disciplines concern themselves with classifying and organizing the "nature of things." Those disciplines go by such names as logicians, taxonomists, philosophers, information architects, computer scientists, librarians, operations researchers, systematicists, statisticians, historians, and so forth. (In short, given our ontos, every area of human endeavor has the urge to classify, to organize.) In each of these areas not only do their domains differ, but so do the adopted structures and classification schemes often used.
There are at least 40 terms or concepts across these various disciplines, most related to Web and general knowledge content, that have organizational or classificatory aspects that — loosely defined — could be called an "ontology" framework or approach:
Actual domains or subject coverage are then mostly orthogonal to these approaches.
Loosely defined, the number of possible ontologies is therefore close to infinite: domain X perspective X schema. (Just kidding — sort of! In fact, UMBC's Swoogle ontology search service claims 10,000 ontologies presently on the Web; the actual data from August 2006 ranges from about 16,000 to 92,000 ontologies, depending on how "formal" the definition. These counts are also limited to OWL-based ontologies.)
Many have misunderstood the semantic Web because of this diversity and the slipperiness of the concept of an ontology. This misunderstanding becomes flat wrong when people claim the semantic Web implies one single grand ontology or organizational schema, One Ring to Rule Them All. Human and domain diversities makes this viewpoint patently false.
Diversity, 'Naturalness' and Change
The choice of an ontological approach to organize Web and structured content can be contentious. Publishers and authors perhaps have too many choices: from straight Atom or RSS feeds and feeds with tags to informal folksonomies and then Outline Processor Markup Language or microformats. From there, the formalism increases further to include the standard RDF ontologies such as SIOC (Semantically-Interlinked Online Communities), SKOS (Simple Knowledge Organizing System), DOAP (Description of a Project), and FOAF (Friend of a Friend) and the still greater formalism of OWL's various dialects.
Arguing which of these is the theoretical best method is doomed to failure, except possibly in a bounded enterprise environment. We live in the real world, where multiple options will always have their advocates and their applications. All of us should welcome whatever structure we can add to our information base, no matter where it comes from or how it's done. The sooner we can embrace content in any of these formats and convert it to a canonical form, we can then move on to needed developments in semantic mediation, the threshold condition for the semantic Web.
There are at least 40 concepts — loosely defined — that could be called an "ontology" framework or approach. |
So, diversity is inevitable and should be accepted. But that observation need not also embrace chaos.
In my early training in biological systematics, Ernst Haeckel's recapitulation theory that "ontogeny recapitulates phylogeny" (note the same ontos root, the difference from ontology being growth v. study) was losing favor fast. The theory was that the development of an organism through its embryological phases mirrors its evolutionary history. Today, modern biologists recognize numerous connections between ontogeny and phylogeny, explain them using evolutionary theory, or view them as supporting evidence for that theory.
Yet, like the construction of phylogenetic trees, systematicists strive for their classifications of the relatedness of organisms to be "natural", to reflect the true nature of the relationship. Thus, over time, that understanding of a "natural" system has progressed from appearance → embryology → embryology + detailed morphology → species and interbreeding → DNA. While details continue to be worked out, the degree of genetic relatedness is now widely accepted by biologists as a "natural" basis for organizing the Tree of Life.
It is not unrealistic to also seek "naturalness" in the organization of other knowledge domains, to seek "naturalness" in the organization of their underlying ontologies. Like natural systems in biology, this naturalness should emerge from the shared understandings and perceptions of the domain's participants. While subject matter expertise and general and domain knowledge are essential to this development, they are not the only factors. As tagging systems on the Web are showing, common usage and broad acceptance by the community at hand is important as well.
While it may appear that a domain such as the biological relatedness of organisms is more empirical than the concepts and ambiguous words in most domains of human endeavor, these attempts at naturalness are still not foolish. The phylogeny example shows that understanding changes over time as knowledge is gained. We now accept DNA over the recapitulation theory.
As the formal SKOS organizational schema for knowledge systems recognizes (see below), the ideas of narrower and broader concepts can be readily embraced, as well as concepts of relatedness and aliases (synonyms). These simple constructs, I would argue, plus the application of knowledge being gained in related domains, will enable tomorrow's understandings to be more "natural" than today's, no matter the particular domain at hand.
So, in seeking a "naturalness" within our organizational schema, we can also see that change is a constant. We also see that the tools and ideas underlying the seemingly abstract cause of merging and relating existing ontologies to one another will further a greater "naturalness" within our organizations of the world.
A Spectrum of Formalisms
According to the Summit, expressiveness is the extent and ease by which an ontology can describe domain semantics. Structure they define as the degree of organization or hierarchical extent of the ontology. They further define granularity as the level of detail in the ontology. And, as the diagram above alludes, they define other dimensions of use, logical basis, purpose and so forth of an ontology.
The over fifty respondents from 42 communities submitted some 70 different ontologies under about 40 terms to a survey that was used by the Summit to construct their diagram. These submissions included:
. . . formal ontologies (e.g., BFO, DOLCE, SUMO), biomedical ontologies (e.g., Gene Ontology, SNOMED CT, UMLS, ICD), thesauri (e.g., MeSH, National Agricultural Library Thesaurus), folksonomies (e.g., Social bookmarking tags), general ontologies (WordNet, OpenCyc) and specific ontologies (e.g., Process Specification Language). The list also includes markup languages (e.g., NeuroML), representation formalisms (e.g., Entity-Relation model, OWL, WSDL-S) and various ISO standards (e.g., ISO 11179). This [Ontolog] sample clearly illustrates the diversity of artifacts collected under "ontology".
I think the simplest spectrum for such distinctions is the formalism of the ontology and its approach (and language or syntax, not further discussed here). More formal ontologies have greater expressiveness and structure and inferential power, less formal ones the opposite. Constructing more formal ontologies is more demanding, and takes more effort and rigor, resulting in an approach that is more powerful but also more rigid and less flexible. Like anything else, there are always trade-offs.
Based on work by Leo Obrst of Mitre as interpreted by Dan McCreary, we can view this as a trade-off as one of semantic clarity v. the time and money required to construct the formalism [12, 13]:
Note this diagram reflects the more conventional, practitioner's view of the "formal" ontology, which does not include taxonomies or controlled vocabularies (for example) in the definition. This represents the more "closely defined" end of the ontology (semantic) spectrum.
However, since we are speaking here of ontologies and the structured Web or the semantic Web, I believe we need to embrace a concept of ontology aligned to actual practice. Not all content providers can or want to employ ontology engineers to enable formal inferencing of their content. Yet, on the other hand, their content in its various forms does have some meaningful structure, some organization. The trick is to extract this structure for more meaningful use such as data exchange or data merging.
Ontology Approaches on the Web
Under such "loosely defined" bases we can thus see a spectrum of ontology approaches on the Web, proceeding from less structure and formalism to more so:
Type or Schema | Examples | Comments on Structure and Formalism | |
Standard Web Page | entire Web | General metadata fields in the and internal HTML codes and tags provide minimal, but useful sources of structure; other HTTP and retrieval data can also contribute | |
Blog / Wiki Page | examples from Technorati, Bloglines, Wikipedia | Provides still greater formalism for the organization and characterization of content (subjects, categories, posts, comments, date/time stamps, etc.). Importantly, with the addition of plug-ins, some of the basic software may also provide other structured characterizations or output (SIOC, FOAF, etc.; highly varied and site-specific given the diversity of publishing systems and plug-ins) | |
RSS / Atom feeds | most blogs and most news feeds | RSS extends basic XML schema for more robust syndication of content with a tightly controlled vocabulary for feed concepts and their relationships. Because of its ubiquity, this is becoming a useful baseline of structure and formalism; also, the nature of adoption shows much about how ontological structure is an artifact, not driver, for use | |
RSS / Atom feeds with tags or OPML | Grazr, most newsfeed aggregators can import and export OPML lists of RSS feeds | The OPML specification defines an outline as a hierarchical, ordered list of arbitrary elements. The specification is fairly open which makes it suitable for many types of list data. See also OML and XOXO | |
Hierarchical Faceted Metadata | XFML, Flamenco | These and related efforts from the information architecture (IA) community are geared more to library science. However, they directly contribute to faceted browsing, which is one of the first practical instantiations of the semantic Web | |
Folksonomies | Flickr, del.icio.us | Based on user-generated tags and informal organizations of the same; not linked to any "standard" Web protocols. Both tags and hierarchical structure are arbitrary, but some researchers now believe over large enough participant sets that structural consensus and value does emerge | |
Microformats | Example formats include hAtom, hCalendar, hCard, hReview, hResume, rel-directory, xFolk, XFN and XOXO | A microformat is HTML mark up to express semantics with strictly controlled vocabularies. This markup is embedded using specific HTML attributes such as class, rel, and rev. This method is easy to implement and understand, but is not free-form | |
Embedded RDF | RDFa, eRDF | An embedded format, like microformats, but free-form, and not subject to the approval strictures associated with microformats | |
Topic Maps | Infoloom, Topic Maps Search Engine | A topic map can represent information using topics (representing any concept, from people, countries, and organizations to software modules, individual files, and events), associations (which represent the relationships between them), and occurrences (which represent relationships between topics and information resources relevant to them) | |
RDF | Many; DBpedia, etc. | RDF has become the canonical data model since it represents a "universal" conversion format | |
RDF Schema | SKOS, SIOC, DOAP, FOAF | RDFS or RDF Schema is an extensible knowledge representation language, providing basic elements for the description of ontologies, otherwise called RDF vocabularies, intended to structure RDF resources. This becomes the canonical ontology common meeting ground | |
OWL Lite | Here are some existing OWL ontologies; also see Swoogle for OWL search facilities | The Web Ontology Language (OWL) is a language for defining and instantiating Web ontologies. An OWL ontology may include descriptions of classes, along with their related properties and instances. OWL is designed for use by applications that need to process the content of information instead of just presenting information to humans. It facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. The three language versions are in order of increasing expressiveness | |
OWL Full | |||
Higher-order "formal" and "upper-level" ontologies | SUMO, DOLCE, PROTON, BFO, Cyc, OpenCyc | These provide comprehensive ontologies and often related knowledge bases, with the goal of enabling AI applications to perform human-like reasoning. Their reasoning languages often use higher-order logics |
As a rule of thumb, items that are less "formal" can be converted to a more formal expression, but the most formal forms can generally not be expressed in less formal forms.
As latter sections elaborate, I see RDF as the universal data model for representing this structure into a common, canonical format, with RDF Schema (specifically SKOS, but also supplemented by FOAF, DOAP and SIOC) as the organizing ontology knowledge representation language (KRL).
This is not to say that the various dialects of OWL should be neglected. In bounded environments, they can provide superior reasoning power and are warranted if they can be sufficiently mandated or enforced. But the RDF and RDF-S systems represent the most tractable "meeting place" or "middle ground," IMHO.
Still-Another "Level" of Ontologies
As if the formalism dimension were not complicated enough, there is also the practice within the ontology community to characterize ontologies by "levels", specifically upper, middle and lower levels. For example, chances are that you have heard particularly of "upper-level" ontologies.
The following figure helps illustrate this "level" dimension. This diagram is also from Leo Obrst of Mitre [12], and was also used in another 2006 talk by Jack Park and Patrick Durusau (discussed further below for other reasons):
Examples of upper-level ontologies include the Suggested Upper Merged Ontology (SUMO), the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE), PROTON, Cyc and BFO (Basic Formal Ontology). Most of the content in their upper-levels is akin to broad, abstract relations or concepts (similar to the primary classes, for example, in a Roget's Thesaurus — that is, real ontos stuff) than to "generic common knowledge." Most all of them have both a hierarchical and networked structure, though their actual subject structure relating to concrete things is generally pretty weak [2].
The above diagram conveys a sense of how multiple ontologies can relate to one another both in terms of narrower and broader topic matter and at the same "levels" of generalization. Such "meta-structure" (if you will) can provide a reference structure for relating multiple ontologies to one another.
The relationships and mappings amongst ontologies is a critical infrastructure component of the semantic Web. |
It resides exactly in such bindings or relationships that we can foresee the promise of querying and relating multiple endpoints on the Web with accurate semantics in order to connect dots and combine knowledge bases. Thus, the understanding of the relationships and mappings amongst ontologies becomes a critical infrastructural component of the semantic Web.
The SUMO Example
We can better understand these mapping and inter-relationship concepts by using a concrete example with a formal ontology. We'll choose to use the Suggested Upper Merged Ontology simply because it is one of the best known. We could have also selected another upper-level system such as PROTON [3] or Cyc [4] or one of the many with narrower concept or subject coverage.
SUMO is one of the formal ontologies that has been mapped to the WordNet lexicon, which adds to its semantic richness. SUMO is written in the SUO-KIF language. SUMO is free and owned by the IEEE. The ontologies that extend SUMO are available under GNU General Public License.
The abstract, conceptual organization of SUMO is shown by this diagram, which also points to its related MILO (MId-Level Ontology), which is being developed as a bridge between the abstract content of the SUMO and the richer detail of various domain ontologies:
At this level, the structure is quite abstract. But one can easily browse the SUMO structure. A nifty tool to do so is the KSMSA (Knowledge Support for Modeling and Simulation) ontology browser. Using a hierarchical tree representation, you can navigate through SUMO, MILO, WordNet, and (with the locally installed version) Wikipedia.
The figure below shows the upper-level entity concept on the left; the right-hand panel shows a drill-down into the example atom entity:
These views may be a bit misleading because the actual underlying structure, while it has hierarchical aspects as shown here, really is in the form of a directed acyclic graph (showing other relatedness options, not just hierarchical ones). So, alternate visualizations include traditional network graphs.
The other thing to note is that the "things" covered in the ontology, the entities, are also fairly abstract. That is because the intention of a standard "upper-level" ontology is to cover all relevant knowledge aspects of each entity's domain. This approach results in a subject and topic coverage that feels less "concrete" than the coverage in, say, an encyclopedia, directory or card catalog.
Ontology Binding and Integration Mechanisms
According to Park and Durusau, upper ontologies are diverse, middle ontologies are even more diverse, and lower ontologies are more diverse still. A key observation is that ontological diversity is a given and increases as we approach real user interaction levels. Moreover, because of the "loose" nature of ontologies on the Web (now and into the future), diversity of approach is a further key factor.
Recall the initial discussion on the role and objectives of ontologies. About half of those roles involve effectively accessing or querying more than one ontology. The objective of "upper-level" ontologies, many with their own binding layers, is also expressly geared to ontology integration or federation. So, what are the possible mechanisms for such binding or integration?
A fundamental distinction within mechanisms to combine ontologies is whether it is a unified or centralized approach (often imposed or required by some party) or whether it is a schema mapping or binding approach. We can term this distinction centralized v. federated.
Centralized Approaches
Centralized approaches can take a number of forms. At the most extreme, adherence to a centralized approach can be contractual. At the other end are reference models or standards. For example, illustrative reference models include:
- the Data Reference Model (DRM), one of the five reference models of the Federal Enterprise Architecture (FEA)
- UDEF (Unified Data Element Framework), an approach toward a unified description framework, or
- the eXtended MetaData Registry (XMDR) project.
Though I have argued that One Ring to Rule them All is not appropriate to the general Web, there may be cases within certain enterprises or where through funding clout (such as government contracts), some form of centralized approach could be imposed [5]. And, frankly, even where compliance can not be assured, there are advantages in economy, efficiency and interoperability to attempt central ontologies. Certain industries — notably pharmaceuticals and petrochemicals — and certain disciplines — such as some areas of biology among others — have through trade associations or community consensus done admirable jobs in adopting centralized approaches.
Federated Approaches
However, combining ontologies in the context of the broader Internet is more likely through federated approaches. (Though federated approaches can also be improved when there are consensual standards within specific communities.) The key aspect of a federated approach is to acknowledge that multiple schema need to be brought together, and that each contributing data set and its schema will not be altered directly and will likely remain in place.
Thus, the key distinctions within this category are the mechanisms by which those linkages may take place An important goal in any federated approach is to achieve interoperability at the data or instance level without unacceptable loss of information or corruption of the semantics. Numerous specific approaches are possible, but three example areas in RDF-topic map interoperability, the use of "subject maps", and binding layers can illustrate some of the issues at hand.
In 2006 the W3C set up a working group to look at the issue of RDF and topic maps interoperability. Topic maps have been embraced by the library and information architecture community for some time, and have standards that have been adopted under ISO. Somewhat later but also in parallel was the development of the RDF standard by W3C. The interesting thing was that the conceptual underpinnings and objectives between these two efforts were quite similar. Also, because of the substantive thrust of topic maps and the substantive needs of its community, quite a few topic maps had been developed and implemented.
One of the first efforts of the W3C work group was to evaluate and compare five or six extant proposals for how to relate RDF and topic maps [6]. That report is very interesting reading for any one desirous of learning more about specific issues in combining ontologies and their interoperability. The result of that evaluation then led to some guidelines for best practices in how to complete this mapping [7]. Evaluations such as these provide confidence that interoperability can be achieved between relatively formal schema definitions without unacceptable loss in meaning.
A different, "looser" approach, but one which also grew out of the topic map community, is the idea of "subject maps." This effort, backed by Park and Durusau noted above, but also with the support of other topic map experts such as Steve Newcomb and Robert Barta via their proposed Topic Maps Reference Model (ISO 13250-5), seems to be one of the best attempts I've seen that both respects the reality of the actual Web while proposing a workable, effective scheme for federation.
The basic idea of a subject map is built around a set of subject "proxies." A subject proxy is a computer representation of a subject that can be implemented as an object, must have an identity, and must be addressable (this point provides the URI connector to RDF). Each contributing schema thus defines its own subjects, with the mappings becoming meta-objects. These, in turn, would benefit from having some accepted subject reference schema (not specifically addressed by the proponents) to reduce the breadth of the ultimate mapped proxy "space."
I don't have the expertise to judge further the specifics, but I find the presentation and papers by Park and Durusau, Avoiding Hobson's Choice In Choosing An Ontology and Towards Subject-centric Merging of Ontologies to be worthwhile reading in any case. I highly recommend these papers for further background and clarity.
As the third example, "binding layers" are a comparatively newer concept. Leading upper-level ontologies such as SUMO or PROTON propose their own binding protocols to their "lower" domains, but that approach takes place within the construct of the parent upper ontology and language. Such designs are not yet generalized solutions. By far the most promising generalized binding solution is the SKOS (Simple Knowledge Organization System). Because of its importance, the next section is devoted to it.
Finally, with respect to federated approaches, there are quite a few software tools that have been developed to aid or promote some of these specific methods. For, example, about twenty of the software applications in my Sweet Tools listing of 500+ semantic Web and -related tools could be interpreted as aiding ontology mapping or creation. You may want to check out some of these specific tools depending on your preferred approach [8].
The Role of SKOS – the Simple Knowledge Organization System
SKOS, or the Simple Knowledge Organization System, is a formal language and schema designed to represent such structured information domains as thesauri, classification schemes, taxonomies, subject-heading systems, controlled vocabularies, or others; in short, most all of the "loosely defined" ontology approaches discussed herein. It is a W3C initiative more fully defined in its SKOS Core Guide [9].
SKOS is built upon the RDF data model of the subject–predicate–object "triple." The subjects and objects are akin to nouns, the predicate a verb, in a simple Dick-sees-Jane sentence. Subjects and predicates by convention are related to a URI that provides the definitive reference to the item. Objects may be either a URI resource or a literal (in which case it might be some indexed text, an actual image, number to be used in a calculation, etc.).
Being an RDF Schema simply means that SKOS adds some language and defined relationships to this RDF baseline. This is a bit of recursive understanding, since RDFS is itself defined in RDF by virtue of adding some controlled vocabulary and relations. The power, though, is that these schema additions are also easily expressed and referenced.
This RDFS combination can thus be shown as a standard RDF triple graph, but with the addition of the extended vocabulary and relations:
The power of the approach arises from the ability of the triple to express virtually any concept, further extended via the RDFS language defined for SKOS. SKOS includes concepts such as "broader" and "narrower", which enable hierarchical relations to be modeled, as well as "related" and "member" to support networks and arrays, respectively [9].
We can visualize this transforming power by looking at how an "ontology" in a totally foreign scheme can be related to the canonical SKOS scheme. In the figure below the left-hand portion shows the native hierarchical taxonomy structure of the UK Archival Thesaurus (UKAT), next as converted to SKOS on the right (with the overlap of categories shown in dark purple). Note the hierarchical relationships visualize better via a taxonomy, but that the RDF graph model used by SKOS allows a richer set of additional relationships including related and alternative names:
SKOS also has a rich set of annotation and labeling properties to enhance human readability of schema developed in it [9]. There is also a useful draft schema that the W3C's SWEO (Semantic Web Education and Outreach) group is developing to organize semantic Web-related information [10].
Combined, these constructs provide powerful mechanisms for giving contributory ontologies a common conceptualization. When added to other sibling RDF schema such as FOAF or SIOC or DOAP, still additional concepts can be collated.
While not addressed directly in this piece, it is obviously of first importance to have content with structure before the questions of connecting that information can even arise. Then, that structure must also be available in a form suitable for merging or connection.
At that point, the subjects of this posting come into play.
We are stubbing our toes on the rocks while we gaze at the heavens. |
We see that the daily Web has a diversity of schema or ontologies "loosely defined" for representing the structure of the content. These representations can be transferred to more complex schema, but not in the opposite direction. Moreover, the semantic basis for how to make these mappings also needs some common referents.
RDF provides the canonical data model for the data transfers and representations. RDFS, especially in the form of SKOS, appears to form one basis for the syntax and language for these transformations. And SKOS, with other schema, also appears to offer much of the appropriate "middle ground" for data relationships mapping.
However, lacking in this story is a referential structure for subject relationships [11]. (Also lacking are the ultimately critical domain specifics required for actual implementation.)
Abstract concepts of interest to philosophers and deep thinkers have been given much attention. Sadly, to date, concrete subject structures in which tangible things and tangible actions can be shared, is still very, very weak. We are stubbing our toes on the rocks while we gaze at the heavens.
Yet, despite this, simple and powerful infrastructures are well in-hand to address all foreseeable syntactic and semantic issues. There appear to be no substantive limits to needed next steps.
Lastly, many valuable resources for further reading and learning may be found within the Ontolog Community, W3C, TagCommons and Topics Maps groups. Enjoy! And be wary of ontology no longer.
[1] Deborah L. McGuinness. "Ontologies Come of Age". In Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003. See http://www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-mit-press-(with-citation).htm
[2] I think it would be much clearer to refer to "upper level" ontologies as abstract or conceptual, "mid levels" as mapping or binding, and "lower levels" as domain (without any hierarchical distinctions such as lower or lowest or sub-domain), but current practice is probably too entrenched to change now.
[3] There are many aspects that make PROTON one of the more attractive reference ontologies. The PROTON ontology (PROTo ONtology), developed within the scope of the SEKT project, is attractive because of its understandability, relatively small size, modular architecture and a simple subsumption hierarchy. It is available in an OWL Lite form and is easy to adopt and extend. On the face of it, the Topic class within PROTON, which is meant to serve as a bridge between different ontologies, may also provide a binding layer to specific subject topics as sub-classes or class instances.
[4] See my earlier post on Cyc.
[5] Even with such clout, it is questionable to get rather complete adherence, as Ada showed within the Federal government. However, where circumstances allow it, central schema and ontologies may be worth pursuing because of improved interoperability and lower costs, even where some portions do not adhere and are more chaotic like the standard Web.
[6] See, A Survey of RDF/Topic Maps Interoperability Proposals, W3C Working Group Note 10 February 2006, Pepper, Vitali, Garshol, Gessa, Presutti (eds.)
[7] See, Guidelines for RDF/Topic Maps Interoperability, W3C Editor's Draft 30 June 2006, Pepper, Presutti, Garshol, Vitali (eds.)
[8] Here are some Sweet Tools that may have a usefulness to ontology federation and creation:
- Adaptiva — is a user-centered ontology building environment, based on using multiple strategies to construct an ontology, minimising user input by using adaptive information extraction
- Altova SemanticWorks — is a visual RDF and OWL editor that auto-generates RDF/XML or nTriples based on visual ontology design
- CMS — the CROSI Mapping System is a structure matching system that capitalizes on the rich semantics of the OWL constructs found in source ontologies and on its modular architecture that allows the system to consult external linguistic resources
- ConcepTool — is a system to model, analyze, verify, validate, share, combine, and reuse domain knowledge bases and ontologies, reasoning about their implication
- ConRef — is a service discovery system which uses ontology mapping techniques to support different user vocabularies
- FOAM — is the Framework for Ontology Alignment and Mapping. It is based on heuristics (similarity) of the individual entities (concepts, relations, and instances)
- hMAFRA (Harmonize Mapping Framework) — is a set of tools supporting semantic mapping definition and data reconciliation between ontologies. The targeted formats are XSD, RDFS and KAON
- IF-Map — is an Information Flow based ontology mapping method. It is based on the theoretical grounds of logic of distributed systems and provides an automated streamlined process for generating mappings between ontologies of the same domain
- IODT — is IBM's toolkit for ontology-driven development. The toolkit includes EMF Ontology Definition Metamodel (EODM), EODM workbench, and an OWL Ontology Repository (named Minerva)
- KAON — is an open-source ontology management infrastructure targeted for business applications. It includes a comprehensive tool suite allowing easy ontology creation and management and provides a framework for building ontology-based applications. An important focus of KAON is scalable and efficient reasoning with ontologies
- LinKFactory — is Language & Computing's ontology management tool. It provides an effective and user-friendly way to create, maintain and extend extensive multilingual terminology systems and ontologies (English, Spanish, French, etc.). It is designed to build, manage and maintain large, complex, language independent ontologies
- M3t4.Studio Semantic Toolkit — is Metatomix's free set of Eclipse plug-ins to allow developers to create and manage OWL ontologies and RDF documents
- MAFRA Toolkit — the Ontology MApping FRAmework Toolkit allows to create semantic relations between two (source and target) ontologies, and apply such relations in translating source ontology instances into target ontology instances
- OntoEngine — is a step toward allowing agents to communicate even though they use different formal languages (i.e., different ontologies). It translates data from a "source" ontology to a "target."
- OntoPortal — enables the authoring and navigation of large semantically-powered portals
- OWLS-MX — the hybrid semantic Web service matchmaker OWLS-MX 1.0 utilizes both description logic reasoning, and token based IR similarity measures. It applies different filters to retrieve OWL-S services that are most relevant to a given query
- pOWL — is a semantic Web development platform for ontologies in PHP. pOWL consists of a number of components, including RAP
- Protege — is an open source visual ontology editor written in Java with many plug-in tools
- Semantic Net Generator — is a utility for generating topic maps automatically from different data sources by using rules definitions specified with Jelly XML syntax. This Java library provides Jelly tags to access and modify data sources (also RDF) to create a semantic network
- SOFA — is a Java API for modeling ontologies and Knowledge Bases in ontology and Semantic Web applications. It provides a simple, abstract and language neutral ontology object model, inferencing mechanism and representation of the model with OWL, DAML+OIL and RDFS languages
- Terminator — is a tool for creating term to ontology resource mappings (documentation in Finnish)
- WebOnto — supports the browsing, creation and editing of ontologies through coarse grained and fine grained visualizations and direct manipulation.
- CollectableProperty — A property which can be used with a skos:Collection
- Collection — A meaningful collection of concepts
- Concept — An abstract idea or notion; a unit of thought
- ConceptScheme — A set of concepts, optionally including statements about semantic relationships between those concepts. Thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', and other types of controlled vocabulary are all examples of concept schemes. Concept schemes are also embedded in glossaries and terminologies.
- OrderedCollection — An ordered collection of concepts, where both the grouping and the ordering are meaningful
- altLabel — An alternative lexical label for a resource. Acronyms, abbreviations, spelling variants, and irregular plural/singular forms may be included among the alternative labels for a concept
- altSymbol — An alternative symbolic label for a resource
- broader — A concept that is more general in meaning. Broader concepts are typically rendered as parents in a concept hierarchy (tree)
- changeNote — A note about a modification to a concept
- definition — A statement or formal explanation of the meaning of a concept
- editorialNote — A note for an editor, translator or maintainer of the vocabulary
- example — An example of the use of a concept
- hasTopConcept — A top level concept in the concept scheme
- hiddenLabel — A lexical label for a resource that should be hidden when generating visual displays of the resource, but should still be accessible to free text search operations
- historyNote — A note about the past state/use/meaning of a concept
- inScheme — A concept scheme in which the concept is included. A concept may be a member of more than one concept scheme
- isPrimarySubjectOf — A resource for which the concept is the primary subject
- isSubjectOf –A resource for which the concept is a subject
- member — A member of a collection
- memberList — An RDF list containing the members of an ordered collection
- narrower — A concept that is more specific in meaning. Narrower concepts are typically rendered as children in a concept hierarchy (tree)
- note — A general note, for any purpose. The other human-readable properties of definition, scopeNote, example, historyNote, editorialNote and changeNote are all sub-properties of note
- prefLabel — The preferred lexical label for a resource, in a given language. No two concepts in the same concept scheme may have the same value for skos:prefLabel in a given language
- prefSymbol — The preferred symbolic label for a resource
- primarySubject — A concept that is the primary subject of the resource. A resource may have only one primary subject per concept scheme
- related — A concept with which there is an associative semantic relationship
- scopeNote — A note that helps to clarify the meaning of a concept
- semanticRelation — A concept related by meaning. This property should not be used directly, but as a super-property for all properties denoting a relationship of meaning between concepts
- subject — A concept that is a subject of the resource
- subjectIndicator — A subject indicator for a concept. [The notion of 'subject indicator' is defined here with reference to the latest definition endorsed by the OASIS Published Subjects Technical Committee]
- symbol — An image that is a symbolic label for the resource. This property is roughly analagous to rdfs:label, but for labelling resources with images that have retrievable representations, rather than RDF literals. Symbolic labelling means labelling a concept with an image.
[10] The SWEO classification ontology is still under active development and has these draft classes. Note, however, the relative lack of actual subject or topic matter:
Classes are currently defined as:
- article – magazine article
- blog – blog discussing SW topics
- book – indicates a textbook, applies to the book's home page, review or listing in Amazon or such
- casestudy – Article on a business case
- conference/event – conferences or events where you can learn about the Semantic Web
- demo/demonstration – interactive SW demo
- forum – a forum on semantic web or related topics
- presentation – Powerpoint or similar slide show
- person – If this is a person's home page or blog, see below
- publication – a scientific publication
- ontology – a formalisation of a shared conceptualization using OWL, RDFS, SKOS or something else based on RDF
- organization – If the page is the home page of an organization, research, vendor etc, see below
- portal – a portal website Semantic Web or related topics, usually hosting information items, mailinglists, community tools
- project – a research (for example EU-IST) or other project that addresses Semantic Web issues
- mailinglist – a mailinglist on semantic Web or related topics
- person – ideally a person that is well known regarding the Semantic Web (people who can do keynote speakers), may also be any related person
- press – a press release by a company or an article about Semantic Web
- recommended – If the resource is seen to be in the top 10 of its kind
- specification – a Semantic Web specification (RDF, RDF/S, OWL, etc)
- categories – (perhaps using tags or other free form annotation
- successstory – Article that can contain advertisment and clearly shows the benefit of semantic web
- tutorial – a tutorial teaching some aspect of semantic web, an example
- vocabulary – a RDF vocabulary
- software project/tool – For product/project home pages
If the page describes an organization, it can be tagged as:
- vendor
- research
- enduser
If the page is a person's home page or blog or similar, it could be:
- opinionleader
- researcher
- journalist
- executive
- geek
The type of audience can also be tagged, for example:
- general public
- beginners
- technicians
- researchers.
[11] The OASIS Topic Maps Published Subjects Technical Committee was formed a number of years back to promote Topic Maps interoperability through the use of Published Subjects Indicators (PSIs). Their resulting report was a very interesting effort that unfortunately did not lead to wide adoption, perhaps because the effort was a bit ahead of its time or it was in advance of the broader acceptance of RDF. This general topic is the subject of a later posting by me.
[12] See further, Leo Obrst, "The Semantic Spectrum & Semantic Models," a Powerpoint presentation (http://ontolog.cim3.net/file/resource/presentation/LeoObrst_20060112/OntologySpectrumSemanticModels–LeoObrst_20060112.ppt)
made as part of an Ontolog Forum (http://ontolog.cim3.net/) presentation in two parts, "What is an Ontology? – A Briefing on the Range of Semantic Models" (see http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2006_01_12), in January 2006. Leo Obrst is a principal artificial intelligence scientist at MITRE's (http://www.mitre.org) Center for Innovative Computing and Informatics and a co-convener of the Ontolog Forum. His presentation is a rich source of practical overview information on ontologies.
[13] The actual diagram is an unattributed modification by Dan McCreary (see http://www.danmccreary.com/presentations/sem_int/sem_int.ppt) based on Obrst's material in [12].


text:
Roasted Stuffed Quail for Two with Madeira Sauce
One of us comes from a family where wild pheasant was served sliced alongside roast turkey at the Thanksgiving table. Since I (Kay) fancied dark meat as a child, it was to my intense dismay when I selected poorly and ended up with stringy, funny-tasting meat riddled with buckshot. Not a great introduction to game.
What a surprise, then, to discover little birds that taste like something reminiscent of a Carolina autumn. Crisp, succulent roasted fowl and woodland flavors echoed in the stuffing of Carolina Gold Rice Grits and Farro Piccolo and favored with a demi glace fortified by Madeira, which represents mankind's highest form of grape artisanship. This dish honors the flavor legacy of grapes and quail, ancient and modern at once. It is a primordial pairing.
If you are not familiar with how much everyone hunts in the South, you might not know that what is hunted is always consumed (no trophy hunting allowed in this neck of the woods). Or that quail, like oysters, are considered finger food, just as is anything easily taken in hand that comes from the wild. Pharaoh quail, the landrace breed we use here, have enough presence to make eating them a carnal adventure. When Southerners eat quail, they don't count.
But you are welcome, of course, to celebrate with proper knife and fork, because quail, a very Southern charmer, can take on airs and civility, dress up, and sit down at the holiday table, too.
Cooking Remarks
We envision this dish as a romantic holiday dinner for two. But it just as easily serves four as a first course.
Manchester Farms, near Columbia, South Carolina, is well known for their consistently humane production of Pharaoh quail and for the nuanced game flavor their little birds carry. Manchester Farms' chef clientele is strictly A-list, and though they could adopt an exclusive and elite attitude, they choose not to do so. We ordered European-style semi boneless birds—a snap to cook and serve.
We do a quick flavoring brine on the quail, which seasons them up very nicely.
equipment mise en place
For the stock reduction, you will need a large heavy-bottomed saucepan.
For prepping the quail, you will need a small saucepan, a shallow 9-inch glass baking dish, and a rimmed baking sheet fitted with a wire rack.
For preparing the stuffing and stuffing and cooking the quail, you will need two medium heavy-bottomed saucepans, a fine-mesh strainer, a glass pie pan or shallow baking dish, two small bowls and a medium bowl, a small heavy-bottomed skillet, butcher's twine, a large ovenproof nonstick skillet, a pair of tongs, and an instant-read thermometer.
For the sauce, you will need a medium saucepan, a wooden spoon, a ladle, and a whisk.
for the stock reduction:
1quart (1 recipe) Rich Homemade Chicken Stock
½Turkish bay leaf
1allspice berry
for the quail:
4semi-boneless quail (see Cooking Remarks)
2cups spring or filtered water
1tablespoon packed light or dark brown sugar
2teaspoons fine sea salt
5garlic cloves, sliced
4strips of peel from 1 navel orange
1teaspoon crushed black peppercorns
1allspice berry
1tablespoon olive oil, to brown the quail
for the stuffing:
6cups spring or filtered water
2ounces (¼ cup) Anson Mills Carolina Gold Rice Grits
Fine sea salt
1ounce (2 tablespoons plus 1 generous teaspoon) Anson Mills Farro Piccolo
2teaspoons unsalted butter
2tablespoons dried currants
1tablespoon 5-year-old Malmsey Madeira
2ounces button mushrooms, wiped or brushed clean
1ounce (about ¼ cup) walnut halves
0.5ounce sliced pancetta, minced (3 tablespoons)
1large shallot, minced (3 tablespoons)
2tablespoons minced flat-leaf parsley
0.5ounce (about 1 tablespoon) lightly beaten egg whites
½teaspoon freshly ground black pepper
for the sauce:
3tablespoons unsalted butter
2tablespoons unbleached all-purpose flour
3tablespoons 5-year-old Malmsey Madeira
Fine sea salt and freshly ground black pepper
Make the stock reduction: Pour the chicken stock into a large heavy-bottomed saucepan. Add the bay and allspice, bring to a simmer over medium-high heat, and reduce the stock until it measures 1⅔ cups. Remove the pan from the heat, cover, and set it aside. (You will be using the stock reduction in both the stuffing and for the sauce.)
Brine the quail: Rinse and dry the quail. Remove any last feathers, if there are any, and trim away any fat. In a small saucepan, heat 1 cup of the water to just below a simmer. Add the sugar, salt, garlic, orange peel, peppercorns, and allspice and stir to dissolve the salt. Pour the liquid into a shallow 9-inch glass baking dish and stir in the remaining 1 cup of water. When the brine has cooled to room temperature, place the quail in the dish; they should be submerged. Transfer the baking dish to the refrigerator (no need to cover) and brine for 1½ hours (fig. 2.1).
Remove the quail from the brine and lay them on a wire rack set over a rimmed baking sheet pan. Slam the rack and baking sheet contraption on the counter several times to drive liquid from the quail, and then refrigerate uncovered for 1 hour or up to overnight.
Prepare the stuffing: While the quail brines and air-dries, adjust an oven rack to the middle position and heat the oven to 200 degrees. Measure 3 cups of water into each of two medium heavy-bottomed saucepans and bring both to a boil over medium-high heat. Add the rice grits and 2 teaspoons of salt to one saucepan, stir, and decrease the heat to medium-low to maintain a gentle simmer; add the farro and 2 teaspoons of salt to the second saucepan, stir, and decrease the heat to medium-low. Cook both uncovered. When the grits are almost tender but for a small center of hard starch, after 8 to 10 minutes of simmering, drain the grits in a fine-mesh strainer and flush them with cold water until cooled. Bounce the grits several times in the strainer to remove excess water, and then distribute them in a glass pie pan or shallow baking dish, dab with the butter, and dry in the oven, stirring occasionally, for 8 to 10 minutes. Let cool. When the farro is just barely tender, after 15 to 20 minutes of simmering, drain it in a fine-mesh strainer and flush with cold water until cooled. Bounce the farro in the strainer to remove excess water, and then set the strainer over a small bowl to allow the grain to drain further.
Turn the currants into a second small bowl, cover with the Madeira, and set aside. Trim the bottom of each mushroom high onto the mushroom cap itself, removing the stem and gills and exposing a solid disk of flesh (fig. 5.1). Slice each cap horizontally into thirds, and then crosshatch each slice into a diminutive brunoise dice (fig. 5.2); you should have about ½ cup. Set the mushrooms aside.
Place the walnuts in a small, heavy-bottomed skillet and toast over medium-low heat, stirring occasionally, until fragrant, about 10 minutes. Let cool slightly and rub the skins away between your palms. Chop the walnuts and set aside.
In the now-empty skillet, cook the pancetta over medium heat, stirring frequently, until the fat renders and the pancetta crisps, about 10 minutes. Add the shallot and sauté until soft and translucent, 5 to 7 minutes. Stir in the mushrooms and cook, stirring frequently, until the liquid they release has evaporated, 4 to 5 minutes. Add 2 tablespoons of the stock reduction and continue to cook until the stock reduces to a glaze. Add the walnuts and currants and sauté briefly. Turn the contents of the skillet into a medium bowl, add the rice grits and farro, and toss to combine. Season with salt to taste and the pepper. Stir in the parsley and egg whites (fig. 7.1) and let cool.
Stuff and truss the quail: Snip four 10-inch lengths of butcher's twine. Working one quail at a time, set the birds on top of a triple thickness of paper towels. Bend each wing tip behind its back and stand the quail on its neck. Swab out the cavity with paper towels. Use a soupspoon to shovel stuffing into the quail (fig. 8.1) and press the stuffing evenly into the breast. Lay the bird on its back and position the butcher's twine at the base of the neck (fig. 8.2). Tightly draw the twine down along either side of the breast (fig. 8.3), securing the wings in place. Pull the twine around and under the legs (fig. 8.4), twist the twine around the ankles, and tie. Trim away the excess twine (fig. 8.5).
With the oven rack still in the middle position, heat the oven to 350 degrees. Heat a large ovenproof nonstick skillet over medium-high heat for 5 minutes. Pour the olive oil into the skillet, swirl to coat the surface, and add the quail. Cook, turning the birds with tongs, until well browned on all sides, 10 to 15 minutes (fig. 9.1). Slide the skillet into the oven and roast the quail until the stuffing registers 150 degrees on an instant-read thermometer, about 5 minutes. Remove the skillet from the oven and let the quail repose in the skillet for 5 minutes (fig. 9.2).
Make the sauce: After putting skillet of the quail into the oven, bring the remaining stock reduction to a simmer over medium heat. Melt 2 tablespoons of the butter in a medium saucepan over medium heat. When it is bubbly, remove the pan from the heat and stir in the flour, and then return the pan to the burner. Cook the roux, stirring constantly, until golden, about 5 minutes. Ladle about ¼ cup of the hot stock into the roux, whisking vigorously to combine; gradually whisk in more stock in increasing amounts. Bring the sauce to a simmer and cook, skimming if necessary, until the sauce is smooth and glossy and thick enough to coat a spoon, about 10 minutes. Stir in the Madeira and whisk in the remaining 1 tablespoon of butter. Season to taste with salt and pepper.
To serve, snip and remove the twine from around the birds. Place each quail on a cutting board, breast up. With a sharp chef's knife, cut the quail in half lengthwise, cleanly through the breast. Place two halves stuffing-side down on each of two dinner plates, and the other two halves stuffing-side up right beside (if serving as a first course, arrange only two halves—one stuffing-side down and one stuffing-side up—on each of four plates). Ladle with sauce and serve hot.
Step photographs by Kathy Rose

subset: commoncrawl


text:
Michael Graves, Princeton's Robert Schirmer Professor of Architecture Emeritus, has been named the recipient of the Topaz Medallion for Excellence in Architectural Education. The medal, from the American Institute of Architects and the Association of Collegiate Schools of Architecture, honors an individual who has made outstanding contributions to architectural education for a decade or more.
Graves, who has been in the forefront of architectural design for 45 years, began teaching at Princeton in 1962 and retired in 2001. He taught architectural design and theory to thousands of undergraduate and graduate architecture students as well as undergraduate students in other disciplines. In his teaching and advising of independent student work, Graves made connections among areas such as urban design, interior design, painting, sculpture and literature. Extending his reach beyond Princeton, he has served as a visiting professor and guest lecturer at numerous schools of architecture around the country and has delivered more than 1,000 public lectures.
Graves built an international reputation as an architect and designer whose works -- ranging from office buildings to single-family homes -- have been credited with introducing historical and contextual themes into modern architecture. His designs for furniture and household items, now sold in national retail stores, have helped bring a higher level of design to everyday objects.
Some of his best-known projects include the Walt Disney Co. corporate headquarters in Burbank, Calif.; the Netherlands' Ministry of Health, Welfare and Sport in the Hague; and the much-celebrated interpretive design scaffolding for the Washington Monument Restoration in Washington, D.C. His 1985 creation of the Alessi teapot with a bird spout instantly made him a star on the home design front.
Graves has won more than 120 other awards and citations, including the National Medal of Arts presented by President Bill Clinton in 1996 for his exceptional achievements in architecture, design and education.
The Topaz Medallion will be presented at the Association of Collegiate Schools of Architecture's annual meeting in New Orleans in March.


text:
KNOXVILLE, Tenn. (AP) — Pat Summitt's family said Sunday that the last few days have been difficult for the former Tennessee women's basketball coach as her Alzheimer's disease progresses.
Amid reports of Summitt's failing health, her family issued a statement asking for prayers and saying that the 64-year-old Summitt is surrounded by the people who mean the most to her. It also asked for privacy.
The statement was posted on the Pat Summitt Foundation's website and was issued by Erin Freeman, a spokeswoman for the Summitt family.
Former Tennessee player Tamika Catchings was flying to Knoxville to visit the coach instead of returning to Indiana with the WNBA's Fever. Other former players and those in the University of Tennessee and the women's basketball communities were issuing support on Twitter through the "PrayForPat" hashtag.
Summitt stepped down as Tennessee's coach in 2012, one year after announcing her diagnosis of early onset dementia, Alzheimer's type. She went 1,098-208 with eight national titles. She has the most career wins of any Division I men's or women's basketball coach.
Since her diagnosis, Summitt has played a leading role in the fight against Alzheimer's. She launched the Pat Summitt Foundation, which is dedicated to researching and educating people about the disease while also providing services to patients and caregivers. The Pat Summitt Alzheimer's Clinic is scheduled to open at the University of Tennessee medical center in December.
"When she fights this disease, what she has taught all of us is how to do it with courage," former Tennessee women's athletic director Joan Cronan said at a 2015 charity event honoring Summitt. "She's done that from Day One. It's been about (how) we can find a cure for this disease, and she has done it facing it straight-on and she's done it giving back as she always has."
Summitt continues to hold a position as head coach emeritus of the Tennessee women's basketball team. She attended nearly every home game and many practices in the first year after stepped down as coach, though she had a less visible role in subsequent seasons. She cut back on public appearances in recent years.


text:
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Your development team wants account-level access to production instances in order to do live debugging of a highly secure environment.
Which of the following should you do?
A. Place the credentials provided by Amazon Elastic Compute Cloud (EC2) into a secure Amazon Sample Storage Service (S3) bucket with encryption enabled.
Assign AWS Identity and Access Management (IAM) users to each developer so they can download the credentials file.
B. Place an internally created private key into a secure S3 bucket with server-side encryption using customer keys and configuration management, create a service account on all the instances using this private key, and assign IAM users to each developer so they can download the file.
C. Place each developer's own public key into a private S3 bucket, use instance profiles and configuration management to create a user account for each developer on all instances, and place the user's public keys into the appropriate account.
D. Place the credentials provided by Amazon EC2 onto an MFA encrypted USB drive, and physically share it with each developer so that the private key never leaves the office.
Answer: C
As part of your continuous deployment process, your application undergoes an I/O load performance test before it is deployed to production using new AMIs.
The application uses one Amazon Elastic Block Store (EBS) PIOPS volume per instance and requires consistent I/O performance.
Which of the following must be carried out to ensure that I/O load performance tests yield the correct results in a repeatable manner?
A. Ensure that the I/O block sizes for the test are randomly selected.
B. Ensure that the Amazon EBS volumes have been pre-warmed by reading all the blocks before the test.
C. Ensure that snapshots of the Amazon EBS volumes are created as a backup.
D. Ensure that the Amazon EBS volume is encrypted.
E. Ensure that the Amazon EBS volume has been pre-warmed by creating a snapshot of the volume before the test.
Answer: B
After reviewing the last quarter's monthly bills, management has noticed an increase in the overall bill from Amazon.
After researching this increase in cost, you discovered that one of your new services is doing a lot of GET Bucket API calls to Amazon S3 to build a metadata cache of all objects in the applications bucket.
Your boss has asked you to come up with a new cost-effective way to help reduce the amount of these new GET Bucket API calls.
What process should you use to help mitigate the cost?
A. Update your Amazon S3 buckets' lifecycle policies to automatically push a list of objects to a new bucket, and use this list to view objects associated with the application's bucket.
B. Create a new DynamoDB table. Use the new DynamoDB table to store all metadata about all objects uploaded to Amazon S3.
Any time a new object is uploaded, update the application's internal Amazon S3 object metadata cache from DynamoDB.
C. Using Amazon SNS, create a notification on any new Amazon S3 objects that automatically updates a new DynamoDB table to store all metadata about the new object.
Subscribe the application to the Amazon SNS topic to update its internal Amazon S3 object metadata cache from the DynamoDB table.
D. Upload all images to Amazon SQS, set up SQS lifecycles to move all images to Amazon S3, and initiate an Amazon SNS notification to your application to update the application's Internal Amazon S3 object metadata cache.
E. Upload all images to an ElastiCache filecache server. Update your application to now read all file metadata from the ElastiCache filecache server, and configure the ElastiCache policies to push all files to Amazon S3 for long-term storage.
Answer: C
Your current log analysis application takes more than four hours to generate a report of the top 10 users of your web application.
You have been asked to implement a system that can report this information in real time, ensure that the report is always up to date, and handle increases in the number of requests to your web application. Choose the option that is cost-effective and can fulfill the requirements.
A. Publish your data to CloudWatch Logs, and configure your application to autoscale to handle the load on demand.
B. Publish your log data to an Amazon S3 bucket.
Use AWS CloudFormation to create an Auto Scaling group to scale your post-processing application which is configured to pull down your log files stored an Amazon S3.
C. Post your log data to an Amazon Kinesis data stream, and subscribe your log-processing application so that is configured to process your logging data.
D. Configure an Auto Scaling group to increase the size of your Amazon EMR duster.
E. Create a multi-AZ Amazon RDS MySQL cluster, post the logging data to MySQL, and run a map reduce job to retrieve the required information on user counts.
Answer: C
You are using Elastic Beanstalk to manage your e-commerce store. The store is based on an open source e- commerce platform and is deployed across multiple instances in an Auto Scaling group. Your development team often creates new "extensions" for the e-commerce store.
These extensions include PHP source code as well as an SQL upgrade script used to make any necessary updates to the database schema.
You have noticed that some extension deployments fail due to an error when running the SQL upgrade script. After further investigation, you realize that this is because the SQL script is being executed on all of your Amazon EC2 instances.
How would you ensure that the SQL script is only executed once per deployment regardless of how many Amazon EC2 instances are running at the time?
A. Use a "Container command" within an Elastic Beanstalk configuration file to execute the script, ensuring that the "leader only" flag is set to true.
B. Make use of the Amazon EC2 metadata service to query whether the instance is marked as the leader" in the Auto Scaling group.
Only execute the script if "true" is returned.
C. Use a "Solo Command" within an Elastic Beanstalk configuration file to execute the script.
The Elastic Beanstalk service will ensure that the command is only executed once.
D. Update the Amazon RDS security group to only allow write access from a single instance in the Auto Scaling group; that way, only one instance will successfully execute the script on the database.
Answer: A
You are administering a continuous integration application that polls version control for changes and then launches new Amazon EC2 instances for a full suite of build tests.
What should you do to ensure the lowest overall cost while being able to run as many tests in parallel as possible?
A. Perform syntax checking on the continuous integration system before launching a new Amazon EC2 instance for build test, unit and integration tests.
B. Perform syntax and build tests on the continuous integration system before launching the new Amazon EC2 instance unit and integration tests.
C. Perform all tests on the continuous integration system, using AWS OpsWorks for unit, integration, and build tests.
D. Perform syntax checking on the continuous integration system before launching a new AWS Data Pipeline for coordinating the output of unit, integration, and build tests.
Answer: B
You are doing a load testing exercise on your application hosted on AWS.
While testing your Amazon RDS MySQL DB instance, you notice that when you hit 100% CPU utilization on it, your application becomes non- responsive.
Your application is read-heavy.
What are methods to scale your data tier to meet the application's needs? Choose 3 answers
A. Add Amazon RDS DB read replicas, and have your application direct read queries to them.
B. Add your Amazon RDS DB instance to an Auto Scaling group and configure your CloudWatch metric based on CPU utilization.
C. Use an Amazon SQS queue to throttle data going to the Amazon RDS DB instance.
D. Use ElastiCache in front of your Amazon RDS DB to cache common queries.
E. Shard your data set among multiple Amazon RDS DB instances.
F. Enable Multi-AZ for your Amazon RDS DB instance.
Answer: ADE
Your mobile application includes a photo-sharing service that is expecting tens of thousands of users at launch.
You will leverage Amazon Simple Storage Service (S3) for storage of the user Images, and you must decide how to authenticate and authorize your users for access to these images.
You also need to manage the storage of these images.
Which two of the following approaches should you use?
Choose 2 answers
A. Create an Amazon S3 bucket per user, and use your application to generate the S3 URI for the appropriate content.
B. Use AWS Identity and Access Management (IAM) user accounts as your application-level user database, and offload the burden of authentication from your application code.
C. Authenticate your users at the application level, and use AWS Security Token Service (STS) to grant token-based authorization to S3 objects.
D. Authenticate your users at the application level, and send an SMS token message to the user.
Create an Amazon S3 bucket with the same name as the SMS message token, and move the user's objects to that bucket.
E. Use a key-based naming scheme comprised from the user IDs for all user objects in a single Amazon S3 bucket.
Answer: CE
You have an Auto Sealing group of Instances that processes messages from an Amazon Simple Queue Service (SQS) queue.
The group scales on the size of the queue. Processing Involves calling a third-party web service.
The web service is complaining about the number of failed and repeated calls it is receiving from you.
You have noticed that when the group scales in, instances are being terminated while they are processing.
What cost-effective solution can you use to reduce the number of incomplete process attempts?
A. Create a new Auto Scaling group with minimum and maximum of 2 and instances running web proxy software.
Configure the VPC route table to route HTTP traffic to these web proxies.
B. Modify the application running on the instances to enable termination protection while it processes a task and disable it when the processing is complete.
C. Increase the minimum and maximum size for the Auto Scaling group, and change the scaling policies so they scale less dynamically.
D. Modify the application running on the instances to put itself into an Auto Scaling Standby state while it processes a task and return itself to InService when the processing is complete.
Answer: D
The operations team and the development team want a single place to view both operating system and application logs.
How should you implement this using AWS services? Choose 2 answers
A. Using AWS CloudFormation, create a CloudWatch Logs LogGroup and send the operating system and application logs of interest using the CloudWatch Logs Agent.
B. Using AWS CloudFormation and configuration management, set up remote logging to send events via UDP packets to CloudTrail.
C. Using configuration management, set up remote logging to send events to Amazon Kinesis and insert these into Amazon CloudSearch or Amazon Redshift, depending on available analytic tools.
D. Using AWS CloudFormation, create a CloudWatch Logs LogGroup.
Because the Cloudwatch Log agent automatically sends all operating system logs, you only have to configure the application logs for sending off-machine.
E. Using AWS CloudFormation, merge the application logs with the operating system logs, and use IAM Roles to allow both teams to have access to view console output from Amazon EC2.
Answer: AC
The project you are working on currently uses a single AWS CloudFormation template to deploy its AWS infrastructure, which supports a multi-tier web application.
You have been tasked with organizing the AWS CloudFormation resources so that they can be maintained in the future, and so that different departments such as Networking and Security can review the architecture before it goes to Production.
How should you do this in a way that accommodates each department, using their existing workflows?
A. Organize the AWS CloudFormation template so that related resources are next to each other in the template, such as VPC subnets and routing rules for Networking and security groups and IAM information for Security.
B. Separate the AWS CloudFormation template into a nested structure that has individual templates for the resources that are to be governed by different departments, and use the outputs from the networking and security stacks for the application template that you control
C. Organize the AWS CloudFormation template so that related resources are next to each other in the template for each department's use, leverage your existing continuous integration tool to constantly deploy changes from all parties to the Production environment, and then run tests for validation.
D. Use a custom application and the AWS SDK to replicate the resources defined in the current AWS CloudFormation template, and use the existing code review system to allow other departments to approve changes before altering the application for future deployments.
Answer: B
You currently run your infrastructure on Amazon EC2 instances behind an Auto Scaling group> All logs for you application are currently written to ephemeral storage.
Recently your company experienced a major bug in code that made it through testing and was ultimately deployed to your fleet.
This bug triggered your Auto Scaling group to scale up and back down before you could successfully retrieve the logs off your server to better assist you in troubleshooting the bug.
Which technique should you use to make sure you are able to review your logs after your instances have shut down?
A. Configure the ephemeral policies on your Auto Scaling group to back up on terminate.
B. Configure your Auto Scaling policies to create a snapshot of all ephemeral storage on terminate.
C. Install the CloudWatch Logs Agent on your AMI, and configure CloudWatch Logs Agent to stream your logs.
D. Install the CloudWatch monitoring agent on your AMI, and set up new SNS alert for CloudWatch metrics that triggers the CloudWatch monitoring agent to backup all logs on the ephemeral drive.
E. Install the CloudWatch monitoring agent on your AMI, Update your Auto Scaling policy to enable automated CloudWatch Log copy.
Answer: C
Management has reported an increase in the monthly bill from Amazon web services, and they are extremely concerned with this increased cost.
Management has asked you to determine the exact cause of this increase.
After reviewing the billing report, you notice an increase in the data transfer cost.
How can you provide management with a better insight into data transfer use?
A. Update your Amazon CloudWatch metrics to use five-second granularity, which will give better detailed metrics that can be combined with your billing data to pinpoint anomalies.
B. Use Amazon CloudWatch Logs to run a map-reduce on your logs to determine high usage and data transfer.
C. Deliver custom metrics to Amazon CloudWatch per application that breaks down application data transfer into multiple, more specific data points.
D. Using Amazon CloudWatch metrics, pull your Elastic Load Balancing outbound data transfer metrics monthly, and include them with your billing report to show which application is causing higher bandwidth usage.
Answer: C
During metric analysis, your team has determined that the company's website is experiencing response times during peak hours that are higher than anticipated.
You currently rely on Auto Scaling to make sure that you are scaling your environment during peak windows.
How can you improve your Auto Scaling policy to reduce this high response time? Choose 2 answers.
A. Push custom metrics to CloudWatch to monitor your CPU and network bandwidth from your servers, which will allow your Auto Scaling policy to have better fine-grain insight.
B. Increase your Auto Scaling group's number of max servers.
C. Create a script that runs and monitors your servers; when it detects an anomaly in load, it posts to an Amazon SNS topic that triggers Elastic Load Balancing to add more servers to the load balancer.
D. Push custom metrics to CloudWatch for your application that include more detailed information about your web application, such as how many requests it is handling and how many are waiting to be processed.
E. Update the CloudWatch metric used for your Auto Scaling policy, and enable sub-minute granularity to allow auto scaling to trigger faster.
Answer: BD
You are responsible for your company's large multi-tiered Windows-based web application running on Amazon EC2 instances situated behind a load balancer.
While reviewing metrics, you've started noticing an upwards trend for slow customer page load time.
Your manager has asked you to come up with a solution to ensure that customer load time is not affected by too many requests per second.
Which technique would you use to solve this issue?
A. Re-deploy your infrastructure using an AWS CloudFormation template.
Configure Elastic Load Balancing health checks to initiate a new AWS CloudFormation stack when health checks return failed.
B. Re-deploy your infrastructure using an AWS CloudFormation template.
Spin up a second AWS CloudFormation stack.
Configure Elastic Load Balancing SpillOver functionality to spill over any slow connections to the second AWS CloudFormation stack.
C. Re-deploy your infrastructure using AWS CloudFormation, Elastic Beanstalk, and Auto Scaling.
Set up your Auto Scaling group policies to scale based on the number of requests per second as well as the current customer load time.
D. Re-deploy your application using an Auto Scaling template.
Configure the Auto Scaling template to spin up a new Elastic Beanstalk application when the customer load time surpasses your threshold.
Answer: C
Your company has multiple applications running on AWS.
Your company wants to develop a tool that notifies on-call teams immediately via email when an alarm is triggered in your environment.
You have multiple on-cal teams that work different shifts, and the tool should handle notifying the correct teams at the correct times.
How should you implement this solution?
A. Create an Amazon SNS topic and an Amazon SQS queue.
Configure the Amazon SQS queue as a subscriber to the Amazon SNS topic.
Configure CloudWatch alarms to notify this topic when an alarm is triggered.
Create an Amazon EC2 Auto Scaling group with both minimum and desired Instances configured to 0.
Worker nodes in this group spawn when messages are added to the queue.
Workers then use Amazon Simple Email Service to send messages to your on call teams.
B. Create an Amazon SNS topic and configure your on-call team email addresses as subscribers.
Use the AWS SDK tools to integrate your application with Amazon SNS and send messages to this new topic.
Notifications will be sent to on-call users when a CloudWatch alarm is triggered.
C. Create an Amazon SNS topic and configure your on-call team email addresses as subscribers.
Create a secondary Amazon SNS topic for alarms and configure your CloudWatch alarms to notify this topic when triggered.
Create an HTTP subscriber to this topic that notifies your application via HTTP POST when an alarm is triggered.
Use the AWS SDK tools to integrate your application with Amazon SNS and send messages to the first topic so that on-call engineers receive alerts.
D. Create an Amazon SNS topic for each on-call group, and configure each of these with the team member emails as subscribers.
Create another Amazon SNS topic and configure your CloudWatch alarms to notify this topic when triggered.
Create an HTTP subscriber to this topic that notifies your application via HTTP POST when an alarm is triggered.
Use the AWS SDK tools to integrate your application with Amazon SNS and send messages to the correct team topic when on shift.
Answer: D
Your company releases new features with high frequency while demanding high application availability.
As part of the application's A/B testing, logs from each updated Amazon EC2 instance of the application need to be analyzed in near real-time, to ensure that the application is working flawlessly after each deployment. If the logs show arty anomalous behavior, then the application version of the instance is changed to a more stable one.
Which of the following methods should you use for shipping and analyzing the logs in a highly available manner?
A. Ship the logs to Amazon S3 for durability and use Amazon EMR to analyze the logs in a batch manner each hour.
B. Ship the logs to Amazon CloudWatch Logs and use Amazon EMR to analyze the logs in a batch manner each hour.
C. Ship the logs to an Amazon Kinesis stream and have the consumers analyze the logs in a live manner.
D. Ship the logs to a large Amazon EC2 instance and analyze the logs in a live manner.
E. Store the logs locally on each instance and then have an Amazon Kinesis stream pull the logs for live analysis.
Answer: C
You have a code repository that uses Amazon S3 as a data store. During a recent audit of your security controls, some concerns were raised about maintaining the integrity of the data in the Amazon S3 bucket. Another concern was raised around securely deploying code from Amazon S3 to applications running on Amazon EC2 in a virtual private cloud.
What are some measures that you can implement to mitigate these concerns? Choose 2 answers.
A. Add an Amazon S3 bucket policy with a condition statement to allow access only from Amazon EC2 instances with RFC 1918 IP addresses and enable bucket versioning.
B. Add an Amazon S3 bucket policy with a condition statement that requires multi-factor authentication in order to delete objects and enable bucket versioning.
C. Use a configuration management service to deploy AWS Identity and Access Management user credentials to the Amazon EC2 instances.
Use these credentials to securely access the Amazon S3 bucket when deploying code.
D. Create an Amazon Identity and Access Management role with authorization to access the Amazon 53 bucket, and launch all of your application's Amazon EC2 instances with this role.
E. Use AWS Data Pipeline to lifecycle the data in your Amazon S3 bucket to Amazon Glacier on a weekly basis.
F. Use AWS Data Pipeline with multi-factor authentication to securely deploy code from the Amazon .5.3 bucket to your Amazon EC2 instances.
Answer: BD
You have an application consisting of a stateless web server tier running on Amazon EC2 instances behind load balancer, and are using Amazon RDS with read replicas.
Which of the following methods should you use to implement a self-healing and cost-effective architecture? Choose 2 answers.
A. Set up a third-party monitoring solution on a cluster of Amazon EC2 instances in order to emit custom CloudWatch metrics to trigger the termination of unhealthy Amazon EC2 instances.
B. Set up scripts on each Amazon EC2 instance to frequently send ICMP pings to the load balancer in order to determine which instance is unhealthy and replace it.
C. Set up an Auto Scaling group for the web server tier along with an Auto Scaling policy that uses the Amazon RDS DB CPU utilization CloudWatch metric to scale the instances.
D. Set up an Auto Scaling group for the web server tier along with an Auto Scaling policy that uses the Amazon EC2 CPU utilization CloudWatch metric to scale the instances.
E. Use a larger Amazon EC2 instance type for the web server tier and a larger DB instance type for the data storage layer to ensure that they don't become unhealthy.
F. Set up an Auto Scaling group for the database tier along with an Auto Scaling policy that uses the Amazon RDS read replica lag CloudWatch metric to scale out the Amazon RDS read replicas. G. Use an Amazon RDS Multi-AZ deployment.
Answer: AD
Your application is currently running on Amazon EC2 instances behind a load balancer.
Your management has decided to use a Blue/Green deployment strategy.
How should you implement this for each deployment?
A. Set up Amazon Route 53 health checks to fail over from any Amazon EC2 instance that is currently being deployed to.
B. Using AWS CloudFormation, create a test stack for validating the code, and then deploy the code to each production Amazon EC2 instance.
C. Create a new load balancer with new Amazon EC2 instances, carry out the deployment, and then switch DNS over to the new load balancer using Amazon Route 53 after testing.
D. Launch more Amazon EC2 instances to ensure high availability, de-register each Amazon EC2 instance from the load balancer, upgrade it, and test it, and then register it again with the load balancer.
Answer: C
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text:
We have supplied overseas customers with products related to capacitor which are Aluminum foil, parts, chemicals, and manufacturing equipments since our establishment. At that time of establishment, international customers are at the dawn of growth, so we have developed together with our customers. In particular, we believe we have built a cooperative relationship with the companies in the field of aluminum electrolytic capacitor in some ways.
In addition, supplying materials and equipments related to Supercapacitor and battery is increased along with rising in energy-related demands of recent years.
Moreover, we have launched food-related business arisen from a network of our customers.
One of our strong points is all of our suppliers' products are first-rate quality. In point of the quality of supplied products, we believe we are not far behind from other suppliers.
The other strong point is having strong international networks we have developed in our history. We have offices in Korea, Taiwan, Shanghai, and Hong Kong and they are managed by a person who is a native of each country. We place first priority on communication with local customers and we have organized a system to quickly meet their demands. Main office in Tokyo has staffs who fluently speak Korean and Chinese and Cantonese, so that our customers can directly communicate with us by their mother language.
Regarding Supply chain, there are production factories for Aluminum foil in Korea, Taiwan, China (near Shanghai) to quickly meet customer's delivery requests.
We continue taking a role as a network for customers by placing emphasis on the trust in a relationship and being based on expertness as a specialized trading company.
取締役 海外営業部長
安野 貴晴
Business Development Dept. has been aggressively expanding and trying new business field without clinging to the existing products and business field we are currently belong to. By taking advantage of our overseas network centering on East Asia, and our strength is that the operation of import/export and domestic delivery can be conducted by own group, we would like to have a business relationship with small and medium-sized companies who have demands such as "What to do for first step of advancing into overseas markets?" or "we want to extend sales more" in the field of manufacturing and sales.
[1] Industrial Chemicals (hydrochloric acid, sulfuric acid, boric acid etc.)
[2] Domestic sales of imported products
[3] Exporting Japanese Manufacturer Products
取締役 開発営業部長
及川 義雄
We have built human resources and a network specialized for business in Asia by locating subsidiary companies, local offices, and agents in China (Shanghai, Hong Kong), Korea, and Taiwan.
Address |
RM No.3203 NEW TOWN CENTER No.83 LOU SHAN GUAN RD., SHANGHAI , CHINA |
Number |
Phone : 86-21-6236-9388 / Fax : 86-21-6236-9918 |
Summary |
We are a trading company whose business is sales of Aluminum foil and other related materials for capacitor, manufacturing equipment, and various electronic materials. In addition, we produce and assemble metal processed products and molded products. Our business is not only exporting or importing products as a trading company. We meet the customers' needs such as transaction with foreign currency and Renminbi, and quick delivery requests by owning a bond warehouse in Shangai Pilot Free Trade Zone. We perform delivery management of materials, selecting materials, researching, and planning for local procurement in China of foreign-capitalized companies or overseas company. In addition, we offer consistent services to our customers on demand such as procuring materials, processing metal parts, processing and assembling molded products, and manufacturing management of finished product, and packing and shipping. We have continued challenging to corresponding diversified international society by having a profound expertness, a broad view, and creativity which satisfy customers. |
総経理 陳 偉
JCK Corporation (Shanghai) Limited was established March in 2001. Our sales items are Aluminum foil and other related materials for capacitor, machine parts, molded products, electronics, and daily necessaries. We do not only just sell items or provide funding as a trading company, but also create and provide additional value by developing various functions Our staffs have working experience in a Japanese trading company and a manufacturer. We provide optimal services by meeting the needs of both customers and suppliers based on the languages skill and rich experience. Our staffs are pillars supporting a company's dream come true. To improve business productivity of each staff, making better work environment and working on challenging jobs with satisfaction are necessary. With the high business productivity, we would like to expand and develop new businesses in a wide field.
We will continue further efforts. We greatly appreciate your support and guidance.
Address |
810 Ho,Achasanro 78 Gil 44,Kwangjin Gu,Seoul Korea |
Number |
Phone : 82-2-546-5034 / Fax : 82-2-546-5061 |
Summary |
Our company established in 1989 as a trading company related to Japan. Meanwhile, our business fields are not only related business of capacitor but also Lithium rechargeable battery, LED and food distribution business and still expand and continue growing up the business. |
Web | http://www.kwtkorea.com/ |
代表理事 呉 圭錫
We are making an effort for customer service under our management vision "customer top priority principle intention" and our business policy "Business based on sincerity and trust".
Also we are now growing up by focusing to seek new business through our constant research and development.
In the background, long-term trusting relationship between eminent Japanese makers and accumulated know-how became our basis.
We will try our best to expand as a global trading company to deal with globalization and contributing for group companies growth and society through cooperating more closely with local group agencies in China, Taiwan and Hong Kong as same as Japan.
Address |
7F, No. 168 FU HSING N. RD., TAIPEI, TAIWAN |
Number |
Phone : 886-2-2719-7699 / Fax : 886-2-2719-6219 |
Summary |
An Chuan Enterprise Co., Ltd. was established in 1958 as a trading company. We initially imported and sold Japanese Audio components. At early stage of electrolytic capacitor industry in Taiwan in the 70's, we built a relationship with Kawatake Electronics Co., Ltd as an agent in Taiwan. We grew up along with electrolytic capacitor industry by dealing with Aluminum foil, other materials, and automatic production equipments for capacitor. As an agent, we introduce and supply with high quality materials and high reliability manufacturing equipments along with latest technological information. As we keep eyes on a new field and information, we continue to make efforts to strengthen the foundation of trust relationship both suppliers in Japan and customers in Taiwan. |
総経理 廖本隆
An Chuan Enterprise Co., Ltd. has been introducing Japanese high quality products and great service into Taiwanese electronic industry for more than 50years based on our management vision "Sincerity and trust" between Japan and Taiwanese industry.
Our company strengthens mutual trust relationship which we have made in long period between customers related to aluminum electrolytic capacitors in Taiwan, customers related to energy and Kawatake Electronics.
We will try our best to supply entire services such as new technical skill, equipment, materials and so on for the purpose of improvement of production technical skills for the industry Furthermore, we will cooperate with each Kawatake group and share the information such as countries commerce and customer needs to develop a new business chance.
We ask you for all Kawatake group for support and cooperation.
As joint investment companies with our parent company, Japan Capacitor Industrial Co., Ltd (JCC), we have manufacturing sites in China, Korea, and Taiwan to maintain a stable supply system for products.
Address |
Number |
Phone : 86-512-5283-6996 / Fax : 86-512-5283-6926 |
Address |
Number |
Phone : 82-43-213-1281~2 / Fax : 82-43-214-9269 |
Web | http://www.k-jcc.com/ |
Address |
Number |
Phone : 82-2-549-6794 / Fax : 82-2-514-1210 |
Address |
Number |
Phone : 886-35-886724 / Fax : 886-35-886724 |
Copyright © 2019 Kawatake Electronics Co., Ltd. All Rights Reserved.


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Blue Man Group Tickets
Astor Place Theatre | New York, New York
Ladies and gentlemen, tickets are now available to see the magnificent Blue Man Group! Coming to Astor Place Theatre on Sunday 9th September 2018, this show is one of the most talked about events of the year, and you can see why! Grab your tickets now!


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Questions about Mars to be addressed by the Mars Surveyor Program
After decades of exploration of Mars, many questions still remain.
- What happened to the water on Mars?
- Has all the water escaped is it hidden in the ground and polar caps?
- What is the present and past climate of Mars?
- What is the crustal history of Mars
- How and when did Mars experience separation and evolution of the surface?
- What caused the surface of Mars to split into two halves (old southern highlands, young northern lowlands)?
- Did the crust of Mars stop evolving, and if so when & why?
- If Mars used to have a thick atmosphere made of CO2, where is all the CO2 now?
- Does Mars have a magnetic field?