text:
Digital Libraries/Metadata

 * Older versions of the draft developed by UNC/VT Project Team (2009-10-07 PDF WORD)

Module name
Metadata

Scope
This module addresses uses of metadata and some specific metadata standards that may be appropriate in the context of a Digital Library (DL), and the development of metadata records for digital objects.

Learning objectives:
Students will be able to:
 * a. Explain the basic principles of the design of metadata schema, and the assignment of metadata values for specific materials.
 * b. Design a metadata schema and assign the values appropriate to materials in a particular digital library.

5S characteristics of the module:

 * a. Structures: Metadata is a means for increasing the structure of data objects.
 * b. Spaces: Many metadata schemas require the existence of data spaces such as namespaces and repositories, and enable the duplication of data between spaces, as in harvesting.
 * c. Scenarios: Different metadata schemas are designed for different use scenarios, such as for administration and preservation.
 * d. Societies: Different metadata schemas are designed for different use cases and communities.

Level of effort required:

 * a. Class time: 3 hour
 * b. Student time outside class:
 * i. Reading before the class starts: 2-3 hours
 * ii. Homework assignment: 1 hour

Relationships with other modules:

 * 3-b: Digitization: Modules 2-b and 4-b should be taught around the same time in the semester.
 * 4-d: Subject description, vocabulary control, thesauri, terminologies: Module 4-b is a prerequisite to 4-d.
 * 8-a: Preservation: Module 4-b is a prerequisite to 8-a.

Prerequisite knowledge required:
Knowledge of the concept of a field, and the difference between structured and unstructured data.

Introductory remedial instruction:

 * a. Introduction
 * i. Item-level vs. Collection-level description: Description of an individual data object or a collection of data objects (e.g., a library collection, online repository, etc.)
 * ii. Original to the digital library vs. translated to Dublin Core (DC): Creating crosswalks between the metadata native to an object or repository and DC.
 * iii. Relationship between a metadata record and an object: One-to-one principle (see below).
 * iv. Embedded vs. Associated metadata: Metadata embedded in the data object (e.g., cataloging-in-publication data in books) or separate from the object (e.g., card catalog cards)
 * v. Resource discovery: Identifying previously unidentified (to the user) data objects.
 * b. Resource Description Framework (RDF)
 * i. An expression in RDF is a “triple,” consisting of a subject, a predicate and an object. A set of RDF triples is called an RDF graph.
 * 1. Subject: The object being described (e.g., the sky).
 * 2. Predicate: An element or field describing the object (e.g., color).
 * 3. Object: The value that the predicate takes on (e.g., blue).

Body of knowledge:
Conduct the Invent object description exercise prior to addressing Dublin Core. If this exercise is not used, substitute a lecture or other classroom activity to cover the same content.

1. Metadata

 * a. Simple definition: Data about data
 * b. More detailed definition:
 * i. Can refer to either a schema for describing data objects, or the data that describes a specific data object.
 * The data object can be arbitrarily large or small: a single item (e.g., item-level description) or an entire collection of materials (e.g., collection-level description).
 * ii. A set of structured fields and the values that populate those fields.
 * iii. May be used for a variety of purposes, including discovery, administration, and preservation of data objects.

2. Dublin Core (DC)

 * a.	DC Principles:
 * i.	Dumb-Down: Any element may be ignored or simplified in describing an object.
 * ii.	One-to-One: A single metadata record describes a single object.
 * b. Data model:
 * i. Machine-processability requires a coherent data model
 * ii. Provides explicit definitions of resources
 * iii. Relates DC principles & practices to the developments outside Dublin Core Metadata Initiative (DCMI)
 * iv. Makes clear the relationship of DC “packages” of information to other metadata “packages”
 * c. Problems with DC:
 * i. Minimalism: both a strength and a weakness
 * ii. Only a few communities have extensions
 * iii. Most search engines ignore META tags
 * d. DC Extensions: May be developed for specific domains and/or user communities.
 * i. Gateway to Educational Materials (GEM): http://thegateway.org/
 * Example elements include: instructional method, standards, duration, frmat, resources, etc.
 * ii. Darwin Core: darwincore.calacademy.org
 * Example elements include: kingdom, phylum, class, order, family, genus, species, scientific name, continent, etc.

3. Namespaces & Repositories

 * a. 3 types of interoperability
 * i. Federation: Metadata records from multiple repositories are collected into a single repository (e.g., WorldCat). This requires the active participation of the host institutions for the multiple repositories.
 * ii. Harvesting: Metadata records from one repository are automatically gathered and deposited in another repository (e.g., Gateway to Educational Materials). As long records are exposed, they may be harvested without the active participation of the repositories’ host institutions.
 * iii. Crosswalks: “Translation” of records across differing schemas (e.g., OCLC Metadata Crosswalk Repository, http://www.oclc.org/research/researchworks/schematrans/default.htm).

4. Administrative Metadata

 * a. Designates information about the provenance, management of digital objects.
 * b. Should enable verification of the integrity, ownership, and authorship.
 * c. Examples of elements (from the DCMI Administrative Metadata Working Group):
 * i. Rights: Information about intellectual property or other rights held in and over the content metadata.
 * ii. Handling: Instructions for handling the administrative metadata schema and the metadata record.
 * iii. Affiliation: The organization with which a named person was associated when involved with the resource.

5. Preservation Metadata

 * a. See module 8a: Approaches to archiving and repository development
 * i. Note: This module is a prerequisite to module 8-a.
 * b. Data necessary to maintain the viability, renderability, and understandability of digital objects over the long term.
 * i. Viability: The digital object’s bit stream must be intact and readable.
 * ii. Renderability: The bit stream must be translatable into a form that can be viewed by human users or processed by computers.
 * iii. Understandability: Contextual information must be provided so that content can be interpreted and understood by users.
 * c.Preservation metadata can be input to preservation processes, and also record the output of preservation processes.
 * d. Examples of elements (from the PREMIS Data Dictionary, v.1.0):
 * i. PreservationLevel: A value indicating the set of preservation functions expected to be applied to the object.
 * ii. Fixity: Information used to verify whether an object has been altered in an undocumented or unauthorized way.
 * iii. Environment: The means by which the user renders and interacts with content. Separation of digital content from its environmental context can result in the content becoming unusable.

6. Harvesting

 * a. Facilitates:
 * i. Reuse: Enables uses of data objects by organizations and services other than the owner.
 * ii. Services: Functionality can be provided to provide web-based services.
 * iii. Communities: Data objects can be shared widely among a community of interest.
 * b. Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH)
 * i. Harvester: a client application that issues OAI-PMH requests.
 * ii. Repository: a network accessible server that can process OAI-PMH requests.
 * iii. Item: a constituent of a repository from which metadata about a resource can be disseminated.
 * iv. Unique Identifier: unambigiously identifies an item within a repository.
 * v. Record: metadata expressed in a single format.
 * vi. Set: an optional construct for grouping items for the purpose of selective harvesting.

7. Educational metadata

 * a. Sharable Content Object Reference Model (SCORM)
 * i. Standardizes:
 * How learning content can be exchanged between systems.
 * How to define the intended behavior and logic of complex learning experiences so content can be reused, moved, searched for, and recontexualized.
 * b. Three parts:
 * i. Overview: about the model, vision and future
 * ii. Content Aggregation Model: how to put learning content together so it can be moved and reused.
 * iii. Run Time Environment: How content is launched and the learner’s progress is tracked and reported back.

8. Semantic Web

 * a. “The Semantic Web is about two things. It is about common formats for integration and combination of data drawn from diverse sources, where on the original Web mainly concentrated on the interchange of documents. It is also about language for recording how the data relates to real world objects.” (quote is from the W3C’s Semantic Web Activity website: http://www.w3.org/2001/sw/ )
 * i. Both of these – common formats and language for representing relationships between real and digital objects – are metadata problems:
 * Common formats for integration and combination of data may be metadata formats.
 * Language for representing relationships between objects is an RDF triple.
 * b. Necessitates the widespread use of ontologies
 * i. Mapping domain knowledge across many domains
 * c. Cyberinfrastructure: Goal of ubiquitous information infrastructure

Resources

 * a. Required readings:
 * i. Weibel, Stuart. (1995). Metadata: The Foundations of Resource Description. D-Lib Magazine, 1(1). http://www.dlib.org/dlib/July95/07weibel.html
 * ii. Duval, E., Hodgins, W., Sutton, S., Weibel, S. L. (2002). Metadata Principles and Practicalities. D-Lib Magazine, 8(4). http://www.dlib.org/dlib/april02/weibel/04weibel.html

 * b. Introduction to metadata
 * i. Duval, Erik. (2002). Metadata Principles and Practicalities. D-Lib Magazine, 8(4). http://www.dlib.org/dlib/april02/weibel/04weibel.html
 * ii. Liddy, Elizabeth. (2005). Metadata: A Promising Solution. EDUCAUSE Review, 40(3), 10–11. http://www.educause.edu/apps/er/erm05/erm0536.asp
 * iii. Weibel, Stuart. (1995). Metadata: The Foundations of Resource Description. D-Lib Magazine, 1(1). http://www.dlib.org/dlib/July95/07weibel.html

 * c. Metadata for DLs
 * i. Duval, E., Hodgins, W., Sutton, S., Weibel, S. L. (2002). Metadata Principles and Practicalities. D-Lib Magazine, 8(4). http://www.dlib.org/dlib/april02/weibel/04weibel.html

 * d. Dublin Core
 * i. Dublin Core Metadata Initiative. Using Dublin Core. http://dublincore.org/documents/usageguide/
 * ii. Dublin Core Extensions
 * GEM 2.0: Element Descriptions: http://www.thegateway.org/about/documentation/metadataElements/

 * e. Namespaces & Repositories
 * i. Grace A. (2003). Developing a Metadata Strategy. Cataloging & Classification Quarterly, 36(3/4), 31-46.

 * f. Administrative Metadata
 * i. Metadata Encoding & Transmission Standard (METS)
 * http://www.loc.gov/standards/mets/
 * ii. Text Encoding Initiative (TEI)
 * Sperberg-McQueen, C. M., Burnard, L. (2002). Guidelines for Text Encoding and Interchange. University of Oxford.

 * g. Preservation Metadata
 * i. Open Archival Information System (OAIS) reference model
 * Consultative Committee for Space Data Systems. (2002). Reference Model for an Open Archival Information System (OAIS), CCSDS 650.0-R-2, Red Book, Issue 2. http://public.ccsds.org/publications/archive/650x0b1.pdf
 * ii. PREMIS (PREservation Metadata: Implementation Strategies)
 * OCLC/RLG PREMIS Working Group. (2005). Data Dictionary for Preservation Metadata: Final Report of the PREMIS Working Group. Dublin, OH: OCLC Online Computer Library Center, Inc. http://www.oclc.org/research/projects/pmwg/premis-final.pdf
 * OCLC/RLG PREMIS Working Group. (2004). Implementing Preservation Repositories for Digital Materials: Current Practice and Emerging Trends in the Cultural Heritage Community. Dublin, OH: OCLC Online Computer Library Center, Inc. http://www.oclc.org/research/projects/pmwg/surveyreport.pdf
 * OCLC/RLG Working Group on Preservation Metadata. (2002). Preservation Metadata and the OAIS Information Model: A Metadata Framework to Support the Preservation of Digital Objects. Dublin, OH: OCLC Online Computer Library Center, Inc. http://www.oclc.org/research/projects/pmwg/pm_framework.pdf

 * h. Metadata for Harvesting
 * i. The Open Archives Initiative Protocol for Metadata Harvesting. http://www.openarchives.org/OAI/openarchivesprotocol.html
 * ii. Metadata Preparation for the Gateway to Educational Materials. http://www.thegateway.org/about/documentation/metadata-preparation/metaprep/

 * i. Metadata for specific DLs
 * i. National Science Digital Library Metadata Primer: http://nsdl.org/collection/metadata-guide.php
 * ii. National Science Digital Library Metadata Registry: http://metadataregistry.org/

 * j. Semantic Web
 * i. Greenberg, J., Stuart Sutton, S., & Campbell, D. G. (2003). Metadata: A Fundamental Component of the Semantic Web. Bulletin of the American Society for Information Science and Technology, 29(4), 16-18. http://www.asis.org/Bulletin/Apr-03/greenbergetal.html
 * ii. Jacob, E. K. (2003). Ontologies and the Semantic Web. Bulletin of the American Society for Information Science and Technology, 29(4), 19-22. http://www.asis.org/Bulletin/Apr-03/jacob.html
 * iii. Miller, E. (2003). Enabling the Semantic Web for Scientific Research And Collaboration. Paper presented at the NSF Post Digital Library Futures Workshop, Chatham, MA. http://www.sis.pitt.edu/~dlwkshop/paper_miller.html

Exercises / Learning activities

 * a. Homework to be completed prior to this lesson:
 * i. Inventing object description exercise, below, can be conducted as a homework assignment: assigned object description as homework prior to class, then discussion takes place in class.
 * ii. Students should bring a brief write-up or notes on their object description to class.
 * iii. This should not be a graded assignment, but just a jumping-off point for in-class discussion.

 * b. Exercise in class (15-20 minutes recommended): Invent object description
 * i. Break up class into small groups.
 * ii. Hand out an object to each group: a book, a newspaper, a coffee mug, a plant, a Star Wars action figure, whatever the instructor has sitting around his or her office, the more diverse the better.
 * iii. Each group should describe their object as completely as possible, so that a user could locate it in a library / museum / archive.
 * iv. Each group should provide their descriptions. Identify elements in common between types of objects & elements unique to specific types of objects.
 * v. Discuss limitations of specific elements: e.g., books have authors, action figures have manufacturers, plants don’t have either.
 * vi. Exercise can be repeated using Dublin Core or, if the course in which this module is taught is project-based, whatever metadata schema is used by the project.

 * c. Discussion questions for the classroom (use at the end of the class session):
 * i. If no search engines use the META tag, what’s the point of metadata?
 * 1. Use for discovery is meaningless if it doesn’t include discovery by search engines?
 * 2. Discovery by better tools than currently exist?
 * 3. Discovery within small collections with homegrown tools?

Evaluation of learning outcomes
Homework to be completed subsequent to this lesson: Describe a digital object.
 * a. This assignment may be performed by students individually or in small groups, though small groups are recommended.
 * b. This assignment assumes that the course in which this module is taught is project-based, in which the students build a small digital library. Students should describe a digital object that will eventually become part of the course project digital library.
 * c. Students should digitize some piece of content relevant to the course project, or take an already-digitized content, and describe it by assigning values to the fields of this metadata schema. (Taking already-digitized content is recommended.)
 * d. Students should select an existing or invent a new metadata schema that can be used in the course project to describe the digital object. (Selecting an existing scheme is recommended.)
 * e. Assignment deliverable: Students or groups should:
 * 1. Select or invent a set of metadata fields appropriate for describing the digital object.
 * 2. Select or invent values to populate those fields.
 * 3. Explain their rationale for selecting or inventing those fields and values.
 * 4. Post their ideas about a metadata schema and field values to an online forum for discussion, and/or discuss in class.

Glossary

 * a. Aboutness: The subject or topic of a document.
 * b. Cyberinfrastructure: New tools and environments for research that make use of high-performance computing and networking to support collection and management of large data sets.
 * c. Darwin Core: A metadata standard designed to facilitate the exchange of information about the geographic occurrence of species and the existence of specimens in collections.
 * d. Encoded Archival Description (EAD): A metadata standard for encoding archival finding aids using Extensible Markup Language (XML).
 * e. Dublin Core (DC): A shorthand term for the Dublin Core Metadata Element Set, the primary work of the Dublin Core Metadata Initiative (DCMI); a set of 15 metadata elements intended to be generic and universally useful for object description.
 * f. Extensibility: A characteristic of DC; the ability for elements to be added to a schema as needed for a particular context or use.
 * g. Gateway to Educational Materials (GEM): A set of metadata elements specific to the domain of education; an extension of DC.
 * h. Interoperability: The ability of two or more systems or components to exchange information and to use the information that has been exchanged.
 * i. Metadata: Data about data; structured description of information objects; used to aid the understanding, administration, and use of information objects.
 * j. Ontology: A data model that represents a set of concepts, and the relationships between those concepts, within a specific domain (as opposed to the definition of the term “ontology” in Philosophy). Often used interchangeably with the term “thesaurus.”
 * k. Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH): A set of protocols for interoperability between data repositories.
 * l. Resource discovery: Identifying previously unidentified (to the user) data objects.
 * m. Sharable Content Object Reference Model (SCORM): A set of standards for interoperability and reusability of web-based learning materials.
 * n. Text Encoding Initiative (TEI): A standard that enables libraries, museums, publishers, and individual scholars to represent texts for online research, teaching, and preservation.

Contributors

 * a. Initial author: Jeffrey P. Pomerantz
 * b. Evaluators: Jane Greenberg

title: Digital Libraries/Metadata


text:
Multidisciplinary studies/Introduction

Introduction
Multidisciplinary studies are required when a field of study, a topic or a problem of research crosses the borders of disciplines, university faculties, schools or departments and even school subjects, as traditionally subjects indicate independent bodies of knowledge. Therefore multidisciplinary or cross-disciplinary is just a tag to make sure that this is a kind of integration and not merging of several fields of interest in the scenery of organized knowledge representations. It could be regarded as a learning project after the course materials/lecture notes have been written up and presented.and Approaches to the study of a discipline or subject of study

The scope of the term multidisciplinary
As expected, the scope of such a course is unusually wide, covering more than one field of study. Typically the fields covered are not part of a composite subject, e.g. neuropsychology, or psychoimmunology, etc., but a treatment of stand-alone disciplines studying the same chunk of reality and applying their own terminology for the same. ''Consequently, these disciplines need to be aligned with respect to the subject matter of their interest and focus. Also, the relevant terminology need to be harmonized or "synchronized" for meaningful use and results.'' The current course will deal with the most generic terms of Philosophy, Psychology, Logic, Linguistics, and Computing. The rationale of such an approach lies in the fact that some problems cannot be solved by looking at them from a single science view, instead, you need to change views and shift viewpoints in order to identify a solution to the problems identified.

Such studies may be broken down into lectures, or lecture notes, which are further divided into subpages.

My plan: to run a multidisciplinary course tentatively entitled "synchronization of thoughts"

Synchronization of thoughts http://en.wikiversity.org/wiki/User:Genezistan/Synchronization_of_thoughts/lecture_1 Synchronization of thoughts/lecture_1 Synchronization of thoughts/lecture_2 Synchronization of thoughts/lecture_3 Synchronization of thoughts/lecture_4 Synchronization of thoughts/lecture_5

A multidisciplinary (maybe the term cross-disciplinary is better) approach is called for when dealing with any subject of such complexity as to defy capture within a single specialization. An example might be thinking (redirected in Wikipedia to) or thought http://en.wikipedia.org/wiki/Thinking. Or with problems, such as breaking the Maya code that defy solution within a single specialization. In the course of finding a solution several methods were tested, because none of the individual disciplines viewpoints offered satisfactory explanations. The exploration into the meaning of the Maya script http://en.wikipedia.org/wiki/Maya_script is a good example.

"Although it was now clear what was on many Maya inscriptions, they still could not literally be read. However, further progress was made during the 1960s and 1970s, using a multitude of approaches including pattern analysis, de Landa's "alphabet," Knorozov's breakthroughs, and others. In the story of Maya decipherment, the work of archaeologists, art historians, epigraphers, linguists, and anthropologists cannot be separated. All contributed to a process that was truly and essentially multidisciplinary. Key figures included David Kelley, Ian Graham, Gilette Griffin, and Michael Coe."

Unfortunately very few people are educated in several disciplines, hence few are able to do multidisciplinary research on their own, and if they have a PhD research proposal, they have difficulties of finding a tutor. All this is due to the unfortunate bipolarization of specialist vs generalist a divide, which indicates that school subjects and disciplines do not care about providing interfaces between their own specialization and others.

Explanation of course name
One of the basic problems in societal living is to synchronize the individual speakers and help them to cooperate. In addition to that effort to synchronize communication, the efforts to synchronize motion (moving about, or communicating again, but in a different sense) like as it is common with animals is also important, especially when moving in groups: like fish, antelopes and birds.

Why do we need to synchronize?

Because every object has its own time and life-cycle, and as we change all the time we have different experience and explanation of life that need to be synchronized/harmonized. A child and an adult have experience and knowledge of the world. This knowledge has to be synchronized and it is done by passing on the cultural heritage, by imitation, by copying the adult behavior. Synchronization is required for survival and there are three factors in human personality and behavior that can be synchronized. These are emotions, reason and will. We shall see later how and why.

Besides, it is becoming evident that the electrical activitise in the brain are and need to be synchronized, which gives you specific details of the realization of thinking in terms of phases, waves and locations activated and affected in the brain.

http://www.leitl.org/docs/public_html/striz/striz.org/docs/brainweb-synchronization-integration.pdf

1. Synchronization

1. Synchronization means an attempt to cause at least two sources, such as one's mind and some learning object to be active, connected and interacting with each other at any moment of time on purpose.

2. The word thought is very vague and insufficiently defined, therefore one of the lectures will focus on providing an adequate definition of thoughts, ideas, notions, etc.

Synchronization is an operation that is very common and results in understanding. Not only films are synchronized (dubbed), or video captions (subtitling), but electric phases, concerted human motion, like in swimming, dancing and marching, etc. Animals also synchronize their movement when moving in flocks, herds or other group formations.

With respect to human beings and the human mind synchronization of feelings and emotions is very important as it helps create compassion, sympathy, the feeling of togetherness and belonging. The oldest way of synchronizing people's souls is music and dance. Since the effect of sounds is immediately perceived, people, even very young children will automatically move their body to follow the rhythm, tone or pattern of movement of other people. it can take the form of a fad or a craze, like flash mob. http://en.wikipedia.org/wiki/Flash_mob http://vimeo.com/1772947

Thus the examples of synchronized behavior, especially those of emotion is best seen in listening to and playing music, especially while in groups. Synchronized will is seen in marching, parades and other mass movements of people. The only place where reason is synchronized at a large scale is learning, especially at school where the main idea is to teach children rationality and rational behavior through understanding learning materials.

Physicists recently started a new area for research into the rules of any synchronization experienced or observed in nature.

2. Thinking

Thinking is very vaguely defined in any source, but it is generally agreed that thinking is a product of "reason", as opposed to "emotion" or "will, which are deemed to be different component of the mind or the soul. This seems to be acceptable as reason is something rational, devoid of feelings or bias, whereas will is assumed to be the component in control of making decisions, sometimes after having a fight of motivation between emotion and reason. Will must be the strongest component as it is needed for action, and action is the result of whatever motivation takes over, be reason or emotion.

Now thinking is therefore a process taking place very fast in the background allowing other foreground activities such as speech or listening go parallel, and it is not identical with using a language. On the contrary, thinking precedes formulating our ideas, which again are not identical with words or any other components of a natural language. Consequently, the quality of thinking, rationality, logic or reason is not a feature of using a language, but that of a wider term, namely behavior. It is sometimes attributed to intelligence, a competence for accommodation and survival as revealed in the behavior of many organisms.

But intelligence itself cannot explain successful survival of individuals or species on a large scale. Intelligence seems to be a capability to connect with other organisms and the environment in general in a dynamic process where greater intelligence means better and wider skills to adapt and to connect than lesser intelligence. All that subject is widely covered by contemporary and classic authors without coming to a common ground and agreement.

Despite the numerous efforts to say something more tangible about thinking than that it is best dealt with under the keyword thought, there is little agreement about the particulars of the process. The difficulties are obvious and with an enhanced interest in cognition and anything cognitive, empirical research is in place to dig the other end of the tunnel and meet the theories and speculations on thinking one day. Pardon me for the metaphor.

In any case, thinking does not lend itself easily to self-observation, yet there is one recent "tag" reflective thinking with an aim to explore the field as a stand-alone subject and that effort may bring some changes to the scenery. I strongly encourage you to read that page before going to our next subject (insert new heading).

Identifying the problems
1. The problem of integrating Foundation Ontologies (see AI, Formal Logic)

The multidisciplinary approach will help to identify a solution for the problem to define a common set of core ontology vocabulary elements and a shared world model. The field ontologies in AI have helped create WordNet, WordNet a collection or database of English words that may be used as keywords or tags to describe knowledge, which is still divided into knowledge about a language (words used to identify chunks of reality) and knowledge about realia (objects in the real world).

The same solution will offer a new approach to NLP problems for Machine Translation purposes. (Problem 3 below)

In addition, it is expected that a different approach to knowledge representation (query and retrieval languages) for library classification purposes (Information or Library Science) is to emerge as a result of the implementation of a new paradigm to describe the integrated human achievement in the fields of Philosophy, Psychology, Linguistics, Non Formal Logic, Cognitive Science and Computer Science with an aim to have a common understanding of reality.

The outline of such an integrated approach is presented with examples of how thinking and thought processes may be broken down into smaller chunks of operations that enable us to understand the limited wealth of relations in additions to the open world of objects and properties. Among others the application of John Dewey's disciplined mind (thinking) will help to highlight how.

2. The problem of harmonizing school subjects and improving thinking skills

The current problems in education where the various school subjects are not vetted against the concordances of their own individual vocabularies, hence each claiming to describe another chunk of reality than the ones presented by other science subjects could be solved by stepping further from simple subject integration (Merging). Besides, the teaching of new subjects such as critical thinking and reflective thinking are not founded by a proper inclusion of non formal logic and logic operations of dimensions other than truth values. Information is also evaluated in terms of applicability, promptness, reliability, currentness, relevance, precision and details, to name just a few. All that is left out from the approach by formal logic to validate knowledge and this is no longer acceptable.

3. The problem of supplying correct Machine Translation products

Attempts to automate translation processes are based on statistical analysis and processes and a bottom up design principle, whereas a more viable way is a top-down design approach, starting out from foundation ontology. In current practices at that level basic and very abstract concepts are not properly defined (e.g. event is one of them), while time itself is not present in such models. Objects, Properties and Relations are however a sufficient set to generate a descriptive tool for any natural language that may be used for the semantic analysis in MT once and for all. The very same set of concepts is suitable for portraying individual and collective knowledge representations that can replace current curricula approach to education and open up an efficient road to teaching fast and forward thinking (Problem 2 above).

The Root Problem
The group of problems above, the list of which is not exhaustive, seem to have a wider problem in common, i.e. connectivity and alignment. Connectivity and alignment in this context of multidisciplinary studies are the issues, solving them calls for the explanation of the categories of some disciplines clearly by looking at the definitions of other terms used by other disciplines. This may also be called lateral thinking as it is an attempt to integrate the knowledge accumulated in the individual fields and create synergy. Therefore interpreting the key categories in the following disciplines will help understand the ways available to solve the more specific problems listed above.

Introduction to the first lecture
This resource material is meant to be peculiar in the sense that it covers a very wide area which is tagged by very general terms. Consequently, at a first glance the subject matter does not seem to be coherent or interrelated enough to be grasped as just one piece of work, or a single message. Such disparate markings of the text, however, should not be taken as an indication of a lesson that is too general to be of any use for practical purposes. On the contrary, this material is intended to provide practical solutions to problems that have not been possible to solve as yet, because we have been looking at them from a very close range. Consequently, our vision of the subject to this date has not been clear.

“Not seeing the woods for the trees” is a very common failure in perception, and it is probably the approach taken by lateral thinking, by choosing a bird’s eye view of the terrain that can help to overcome such a deadlock situation. Nevertheless, the treatment of the subject will call for occasional zooming on to some terms to show more details for clarification and concretization. Knowledge has always to be specific to be of any use, whereas thinking itself is a very vague term. I am trying to summarize my ideas about the subject under the tautological tag Reflective Thinking as from various sources that phrase may sound familiar to the reader.

Describing a panorama view or presenting a long range view of a complex subject matter is best explained by the trivia that everything is connected to everything, and most of us cannot imagine how seemingly disparate disciplines may be and should be linked together. On the other hand, when you are dealing with a subject matter portrayed in high resolution, or at a very poorly detailed scale, you are likely to find more points to connect up with topics outside that subject or focus, since the more specific and detailed you are, the more limited and less numerous your connections with distant areas would become. This idea will be detailed later under the meaning of the concepts specific and generic.

In assessing very large subjects or covering a very long period of time you need to use an aspect that is wide enough to cover the issue from the beginning to the end, in other words which spans through a whole area or life cycle without a need to go into details or a multitude of issues. By doing so, you can unify subjects that scientists are engaged to explore in more and finer details and not really being bothered about the success of bringing anything directly useful in solving problems in the wider society, or for use outside the academia. If your subject has no boundaries, such as infinity or eternity, then you are likely to end up with the concept of one, an undivided entity, the only thing of which you can say is, that it is bigger than anything you can think of or have experience of. And that idea itself is incomprehensible for a finite mind such as mine.

But if you come to the conclusion that even the biggest thing conceivable has a limit to its size, the your next question pops up how all this increase in size has been formed: whether it is working top down or bottom up, whether the egg or the chicken came first, etc. So you see all those thoughts ad questions are deeply embedded in our concept of spacetime, which has been relatively recently completed with the concepts of motion, energy and work (route, distance), but which terms are not really thought of in everyday discussions.

The model or example for the layout of the book by Schwartz “Definitions, Dictionaries, and Meanings” that I have in mind is available here.

Societal life requires all the three components of the human consciousness or the human mind, namely reason, emotion and will, to be synchronised in order to maintain the smooth operation and organic development of human communities. It also calls for certainty and an origo or a reference point of experience that needs to be verified against shared records of knowledge. Music is a good example how emotions can be used to create communities of accord, elections are a meagre example of how will may be synchronised in the hope of realising a future wanted in the form of a vision presented by the people in or aspiring to power.

Reason is said to be synchronised through logic, learning and knowledge, including classification systems, all to be debated everyday and challenged by common sense, experience and the outcome of human endevours. But reason and rational activity are feared to be on the decline in the general human exercise as emotions, especially excitements are sought at an increasing rate the world over. Time seems to be a rare commodity and contemplation and meditation in dialogues are a luxury. Thinking deep however may have a lot more in store than looking for immediate satisfaction or seeking thrill as opposed to exercising systematic curiosity.

This resurce material is going to be written in wiki form and a hypertext format, because of the varied vocabulary to be used in it that may not be evenly known to all the readers. The resource is also an experiment to show how procedural knowledge may be more useful than lexical knowledge which is examplified by such collections of facts and statements as found in encyclopedias, dictionaries, etc. including the popular (and sometimes pain in the ass) Wikipedia. Having the ideas in here in hypertext fromat is expected to yield special benefits for the readers, as for instance some of the conclusions are aimed to attract the attention of the current practitioners of MT software design saying that all what we have today in terms of MT technologies may be changed for the better, if we can agree on some principles to be outlined in here later. Similarly, those involved in curriculum design and the audit of learning materials may also find it useful.

This writing is peculiar, because its approach to problems and reality does not concern such evident and practical issues as the usual drive for making profit or a career, discussing the feasibility of any plan or theory supported by sponsors, or taking sides with any force in power to help new ideas materialise, etc. No. I address some other basic facts of life as we know them today around the world. I am not interested in establishing a faith school, or joining the current fights over the division of meaning of life to six billion people. I am only interested in describing a theoretical solution to a number of problems that have not been solved by following the traditional paradigm describing human knowledge representations, and the so called facts. In my view if a problem has a theoretical solution, especially when it has a solution for a number of problems, then it is the current practices that must be reviewed to see if the theory is good enough for implementation. If it is, then it is just a question of time to see how an idea that first looks an utopy is going to materialise in due course as a necessity for anything invented as a treatment to a malady.

One final word of remark. It is always a dilemma what to teach. To teach what life is about is not the same as teaching any science or discipline as essential knowledge for living. Life is about getting on in society, among people with different status and motivation, with competing spirit and supportive inclination, with attractions and repulsions, amidst dangers and pleasures, exposed to ageing and illnesses, driven by intuition and instinct and controlled by emotions and reason. Well, you do not expect me to be involved in that, do you? The Landscape

Each educational resource is supposed to cover a subject, a single theme or a broad subject matter, if it is to address comprehensive questions. My work is intended to be multi-disciplinary, or cross-disciplinary, so it is going to discuss issues spreading over more than one disciplines. „What are these subjects and how many of them are there?” - you may want to know in advance.

Well, the answer to that question may be put forward in the form of a cloud of tags that are nowadays used in place of keywords or idex words. I agree, that it is a good point to define your boundaries of meandering, and it is always useful to give an account of anything to be enumerated in advance. So here is a list of topics so that we can have an inventory.

The primary objects or subjects covered in the focus of my analysis are

1.	Categories of Psychology: including

Cognition, Thinking, Mind, Body, Soul, Self, Environment, and Knowledge. Emotion, Will, Reason, Chunking, Focusing. Anticipation, Search, Hit and Match. Mental Operations. Representation of Knowledge as locations in the brain.

2.	Categories of Computing, including

Data and information. Sorting. Recursion. Representation of Knowledge in writing in 2D. Lexical knowledge vs Procedural knowledge. Specific and Generic, Concrete and Abstract. Representation of Knowledge in a computer as BOM lists.

3.	Categories of Algebra: including

Numbers, One, Totality, Absolute, Relative, Integers. Algebraic Operations Properties of addition, substraction, multiplication and division.

4.	Categories of Philosophy: including

Existence, Universe, Infinity, Life and Death, Material, Spirit, Creation. Form and Content, Quality and Quantity.

5.	Categories of Logic: including

Relations, Objects, Properties, Events, etc. Definitions, Sequencing, Proposition, Recursion.

6.	Categories of Linguistics: including

Meaning. Context. Name giving and definition Translation. Clauses. Parts of Speech, Verb, Noun, Headings and Messages, Sentences. Dictionaries. Wordnet.

7.	Categories of Physics: including

Reality, Space, Time, Motion, Universe, Material, Energy, Information.

But they will not be treated in the above grouping. Instead, I am going to combine the topics in a manner that I find coherent and illuminating. So I am going to divide my material in four parts or four territories, as follows in next chapters.

Now the categories above are created by human thinking driven by analysis getting to know more and more about less and less. Not exactly, as the concepts cover objects that are huge and others that are tiny. And the amount of "knowledge", the representations of our findings is growing exponentially. So we have a problem of orientation, finding our way in a secondary version of reality, among the duplicates of the primary input, one of which is now available on computers designed to help to find a common denominator between different disciplines through the use of mathematics, or more precisely, numbers and algebra, the use of which is common to nearly all disciplines.

But "going metric" to become or to sound more scientific is one thing and to enable the lay people understand what good a particular discipline has for the public is another. The divide with the advent of computer is growing wider, so finding a method to describe how we think and how we have created this wealth of knowledge is the next thing to do, if we believe in the principles and values of education.

see Lecture 1:

http://en.wikiversity.org/wiki/User:Genezistan/Synchronization_of_thoughts/lecture_1

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Multidisciplinary studies/Introduction


text:
UTPA STEM/CBI

Challenge Based Instruction
A challenge begins with an open-ended problem which is followed by an opportunity for students to generate ideas. Through discussion students will encounter various perspectives in regards to the issue and can then reform their ideas for a decision in which they feel is better suited for the problem. Through this approach, the facets of knowledge-, learner-, community-, and assessment-centeredness come into play.

title: UTPA STEM/CBI


text:
Legacy cycle

The Legacy Cycle is a process students go through in order to solve a problem. We plan on introducing our students to the process as early on during their education as possible so that they may eventually use this process habitually when solving problems. In this process, the student is first given the problem and asked to generate ideas for this problem and converse with others to improve their ideas by focusing on the “best” answers. Next, a solution is chosen, researched, and modified. This solution is then tested and perfected such that the final answer can be presented to the class. The student will then be asked to evaluate their own work and provide suggestions for others who may be presented with the same problem in the future.

Curriculum Development Process
Legacy Cycles Challenge Based Instruction modules will be designed such that the instructor will

 * 1) Analyze course and module objectives
 * 2) Develop the taxonomy of knowledge for the course
 * 3) Analyze student needs and obstacles to learning
 * 4) Design instruction for a legacy cycle for each challenge, methods for students to generate ideas, materials for multiple perspectives, and research and revise activities
 * 5) Develop formative assessment
 * 6) Develop summative assessment instruments utilizing all 3 levels of questioning

title: Legacy cycle


text:
UTPA STEM/Instructors

Adame, Esmeralda (STC)
Beginning Machining - Hand Tools

Addo-Mensah, Alfred
Chemistry - Stoichiometry

Ahn, Dr. Seokyoung (UTPA)
Statics - Force Equilibrium

Amro, Hanan (STC)
Calculus - Applied Optimization

Andaverdi, Saul (UTPA)
Algebra - Motion Problem

Austin, Jacquelyn (UTPA)
MEMS &NEMS - Atomic Force Microscope

Azarbayejani, Dr. Mohammad (UTPA)
Design of Steel Structures - Compression Members

Babu, Christy (LCC)
Algebra - Functions

Balogh, Dr. Andras (UTPA)
Applications of Trigonometric and Inverse Trigonometric Functions

Bandyopadhyay, Debasish (UTPA)
Organic Chemistry - Chromatography

Beall, Stewart (UTPA)
MEMS & NEMS - Atomic Force Microscope

Bede, Barnabas (UTPA)
Calculus - Taylor Series

Bhatti, Muhammad (UTPA)
Physics (Calculus Based) - Faraday's Law of Electromagnetism

Brush, Dr. Tim (UTPA)
Comparative Embryology - Birth Defects and Their Causes

Bullard, James (UTPA)
Chemistry - Molecular Structure

Butler, Dr. Alley (UTPA)
Engineering Economics - Using Methods of Project Assessment

Caruntu, Dr. Dumitru (UTPA)
Calculus - Integration

Engineering Analysis - Second Order Differential Equations with Applications in Engineering

Castaneda, Jeffrey (TAMIU)
Business Calculus - Limits

Castillo, Dr. Karina (STC)
Chemistry - Chemical Reactions

Chakraborty, Dr. Santanu (UTPA)
Probability and Statistics - Statistical Inference on Mean

Chebotko, Artem (UTPA)
Databases - Partitioning

Choutapalli, Dr. Isaac (UTPA)
Measurements an Instrumentation - Probability & Statistics

Chipara, Mircea (UTPA)
Quantum Mechanics - Particles for Waves

Chu, Dr. Yul (UTPA)
Microprocessor Systems - Cache Memory Design

Microprocessor Systems - Microprocessor System Design

Microprocessor Systems - Number Representation

Cordoba, Joana A. (STC)
Biology - The Cell

Corpuz, Edgar (UTPA)
Physics (Calculus Based) - DC Circuits

Crown, Dr. Stephen W. (UTPA)
Critical Thinking Skills

Graphics - Introduction to CAD

Measurements and Instrumentation - Temperature Measurement

Thermodynamics - The First Law for Closed Systems

Thermodynamics - The First Law for Open Systems

Curts, Dr. Jaime (UTPA)
Educational Testing and Measurement - Classical Item Analysis

Dean, Frank (UTPA)
Chemistry - Gravity and Atmospheric Pressure

Dietrich, Gustavo (UTPA)
Computer Science - Repitition

Dirrigl, Jr., Dr. Frank J. (UTPA)
Environmental Impact Assessment - Map, Compass, and GPS Skills

Dong, Wenjie (UTPA/UTRGV)
Circuits - Laplace Transform

Edingbarough, Dr. Immanuel (UTRGV)
Fundamentals of Product Design - Design Concept Generation

Feng, Dr. Bao-Feng (UTPA/UTRGV)
Calculus - Representing Functions as Power Series

Calculus - Inverse Trigonometric Functions

Calculus II - Trigonometric Integrals and Substitutions

Fredensborg, Brian (UTPA)
Animal Parasitology - Parasite Distribution

Freeman, Dr. Robert A. (UTPA/UTRGV)
Dynamics - The Big Slip

Fu, Bin (UTPA)
Computer Science - Algorith Design

Fuentes, Dr. Arturo A. (UTPA/UTRGV)
Statics - Truss Bridge

Galstyan, Anahit (UTPA)
Probability and Statistics - Binomial Distribution

Galvan, Raul (STC)
Biology - Blood Circulation

Garza, Rommel (STC)
Algebra - Right Triangle Problems

Gassem, Gassem (STC)
Physics (General) - Projectile Motion

Grabowski, Laura (UTPA)
Computer Science - Selection

Guerrero, Dagoberto Jr. (LCC)
Trigonometry - Angles of Elevation and Depression

Gutierrez, Jose J. (UTPA)
Redox Reactions of Organic Compounds

Gutierrez, Judy (TAMIU)
Physics (General) - Torque

Gutierrez, Rosa E. (STC)
Algebra - Logarithmic Functions

Han, Aijie (UTPA)
Chemistry - Magic Blue Bottle

Hilsenbeck, James (UTB)
Business Algebra - Financial Models

Huber, Tim (UTPA)
Business Algebra - Linear Programming

Huq, Hasina (UTPA)
Introduction to VLSI

Jimenez, Abraham (UTB)
Business Algebra - Financial Models

Jorgensen, Kameron (TAMIU)
Chemistry - Stoichiometry

Knobel, Roger (UTPA)
Business Math - Compound Interest and Annuities

Contemporary Mathematics - Voting and Social Choice

Probability and Statistics - Statistics

Kuang, Weidong (UTPA)
Digital Systems

Kypuros, Dr. Javier A. (UTPA)
Numerical Methods and Statistics - Loop and Case Structures

Lee, Dr. Kevin H. (UTPA)
CAM - PLC Programming # 1

CAM - PLC Programming # 2

Lieman, Jonathan (UTPA)
Cell Biology - Cancer Biology

Li, Dr. Huaien (UTPA)
Calculus - Limits

Liu, Fang (UTPA)
Computer Networks - Socket Programming

Liu, Yang (UTPA)
Computer Science - CPU Design

Lopez, Mario A. (STC - Starr County Campus)
Physics (General) - Work & Energy

Macossay, Javier (UTPA)
Introduction to STEM - Batteries From Coins

Introduction to STEM - Cold and Hot Packs

Introduction to STEM - DNA Extraction

Introduction to STEM - Polymers

Introduction to STEM - Preparation of Soap

Introduction to STEM - UV Sensitive Beads

Makaya, Jocob (TAMIU)
Calculus - Right Triangles: Applications

Maldonado, Sofia Carolina (TAMIU)
Engineering Economics - Depreciation Methods

Mandal, Hari D. (TAMIU)
Organic Chemistry - Molecular Shapes

Martinez, Selinda (TAMIU)
Life Sciences, Survey of - Genetics

Materon, Dr. Luis (UTPA)
Microbiology - Genetic Engineering Using Bacteria

Mihut, Dr. Dorina (UTPA)
Engineering Materials - Thin Films

Morales, Daniel A. (STC)
Computer Numerical Controls - Intro to Computer Numerical Controls

Nambiar, Dr. Rajiv (UTPA)
Manufacturing Processes - T-Statistic

Nguyen, Mau Nam (UTPA)
Business Calculus - Optimization Applications

Nguyen, Nam (UTPA)
The Mathematics of Apportionments

Odeh, Dr. Murad (STC)
Microbiology - Chemiosmosis in Eukaryotes

Onica, Dr. Constantin (UTPA)
Calculus - Inverse Trigonometric Functions

Park, Dr. Young-Gil (UTPA)
Thermal Systems Design and Optimization - Economics

Patitz, Matt (UTPA)
Assembly Programming - Exception Handling

Peng, Jun (UTPA)
Microprocessor Systems - Number Representation

Perez, Gustavo (Region One Education Service Center)
Biomedical - Emergency Response Robot - Human Body Systems

Pierce, Virgil U. (UTPA)
Calculus - Modeling Periodic Behavior

Potter, Gregory (UTPA)
Graphics - Introduction to Multi-view Drawings - Snap Cubes

Graphics - Introduction to Pictorial Drawings - Snap Cubes & Special Graph Paper

Graphics - A Lesson in Sub-Assemblies - CAD - Snap Cubes

Graphics - A Lesson in Sub-Assemblies & Working Drawings - CAD - Lincoln Log House

Qiao, Zhijun (UTPA)
Graduate Seminar - Maxwell Model

Rai, Lily (STC)
Calculus - Solving Right Triangles

Rai, Dr. Rajendra P. (UTPA)
Calculus - Mean Value Theorems

Reilly, Christine (UTPA)
Computer Science - Arrays

Rivera (*) (UTPA)
Algebra - Work Problems

Rodriguez, Favio (ECHS)
Algebra - Slope and Linear Functions

Rubio, Amede (UTPA)
Botany - Nutrient Transport, Cycling and Storage

Santos, Cesar (LCC)
Algebra - Exponential Growth Regression

Sarkar, Dr. Kamal (UTPA)
Engineering Materials - Material Properties

Schweller, Robert (UTPA)
Data Structures and Algorithms - NP-Completeness

Setayesh, Shaghayegh (UTB)
Business Algebra - Financial Models

Smith, Dr. K. Christopher (UTPA)
Electrochemistry

Son, Jae Sok (UTPA)
Communication Theory - Noise

Tarawneh, Dr. Constantine (UTPA)
Introduction to Mechanical Engineering - Engineering Estimation

Terry, Matthew (UTPA)
Surface Area to Volume Ratio (for Application in general biology)

Teter, Diane (STC)
Nutrition - Enzymes

Timmer, Dr. Douglas (UTPA)
Introduction to Mechanical Engineering - Process Improvement

Tomai, Emmett (UTPA)
Computer Science - Linked Lists

Tsay, JengJong (UTPA)
Geometry - Properties of Area of Triangles

Differentiation and Derivatives

Vasquez, Dr. Horacio (UTPA)
Mechatronics - Basic Electronics

Statics - Truss Bridge

Mechatronics - Thermocouples, Amplifiers and Comparators

Villalobos, Cristina (UTPA)
Calculus - Applied Linear Algebra

Villarreal, Dr. John (UTPA)
Chemistry - Limiting Reagent:Theoretical Yield

Vitek, Christopher (UTPA)
Aquatic Entomology - Understanding Populations

Watkins, Dr. Will (UTPA)
Legacy Cycles

Graphing

Derivative Algorithm

WFFs, Algebraic Expressions, and Derivatives

Why Derivatives Work

Kidnapper's Headquarters

Derivative Car Trip

Whelen, Dr. Tom (UTPA)
Environmental Chemistry - From Corn to Ethanol

Whitfield, Charles A. (TAMIU)
Business Algebra - Future Value of an Annuity - Sinking Funds

Wilson, Dr. Aaron T. (UTRGV)
Mathematics Teaching and Learning - Mathematical Knowledge for Equitable Teaching

Yanev, George (UTPA)
Probability and Statistics - Binomial Distribution

Yin, Wei (STC)
Calculus II - Trigonometric Integrals and Substitutions

Zeng, Dr. Liang (UTPA)
Physics (Calculus Based) - 1-D Motion

Physics (Calculus Based) - 2-D Non-Rotational Motion

Physics (Calculus Based) - Angular Momentum and its Conservation

Physics (Calculus Based) - Circular Motion

Physics (Calculus Based) - Fluids Mechanics

Physics (Calculus Based) - Linear Momentum and Collisions

Physics (Calculus Based) - Oscillatory Motion

Physics (Calculus Based) - Static Equilibrium and Elasticity

Physics (Calculus Based) - Universal Gravitational Force

Physics (Calculus Based) - Waves and Vibrations

Physics (Calculus Based) - Work Energy Theorem and the Conservation of Energy

Physics (Calculus Based) - Vectors and Free Body Diagrams

Zieschang, Paul-Hermann (UTB)
Calculus - Networks

-

title: UTPA STEM/Instructors


text:
Digital Libraries/Architecture overview

 * Older versions of the draft developed by UNC/VT Project Team (2009-10-07 PDF WORD)

Module name
DL architectures

Scope
This module covers architectures of digital libraries (DLs) such as federated architecture, distributed architecture, and service-oriented architecture, which appear in the DL literature.

Note: Implementation details are not included here.

Learning objectives:
By the end of this module, the student will be able to:
 * a. Be able to distinguish different types of DL architectures mentioned in the scope description section.
 * b. Be able to write specifications for a DL of a particular type of architecture, given a particular context and a particular set of needs.

5S characteristics of the module:
DL architectures are derived from the more conceptual DL models, which contain all the 5Ss as their components. Therefore, these architectures address all the components of the 5S Framework.

 * a. Streams: there are specifications about what type of digital objects can be stored or provided by the DL architecture/models.
 * b. Spaces: storage space and user interfaces are present in the DL architectures/models.
 * c. Scenarios: There are series of steps to go through for each component of DL architectures, and models to communicate with other components; these constitute scenarios.
 * d. Societies: this is not strongly present here, however, the architects and the DL model developers represent the Societies component of the 5S Framework.
 * e. Structures: DL architectures and models have structures, sometimes in layers. Each component of them such as a repository also has a structure.

Level of effort required:

 * a. Class time: 2.5 hour
 * 1 hour for the lecture, 1.5 hours for group presentations and Q/A session
 * b. Student time outside class: 6-8 hours
 * Reading the assigned papers, preparation for group presentations, creation of concept maps for different DL architectures and models

Relationships with other modules:

 * 1-a (10-c): Conceptual frameworks, theories, definitions
 * 5-b: Application software
 * Knowing the conceptual framework and definitions will help with understanding of DL architectures and models.
 * By studying the three modules, 1-a(10-c), 5-a, and 5-b, students might be able to understand DLs from the conceptual level to the real-life systems level. Therefore, it is recommended to teach/learn the above three modules in the order 1-a, 5-a, 5-b.

Prerequisite knowledge required:

 * a. None

Introductory remedial instruction:

 * a. None

Topic: Principles of DL architecture

 * 1. All of these principles are covered in more depth in other modules. But it’s worth covering them briefly here because all DL application development is based on these principles.

 * 2. Kahn & Wilensky (1995) “provides a method for naming, identifying and/or invoking digital objects in a system of distributed repositories” (section 5, ¶ 1), and provided definitions of many important entities in DLs (e.g., digital object, handle, metadata, repository).
 * a. DLs are merely one example of a digital information service, according to Kahn & Wilensky’s framework.

 * 3. Arms’ (1995) General Principles for DL Architecture:
 * a. The technical framework exists within a legal and social framework.
 * i. E.g., music
 * Copyright owners want to maintain control over how content is used.
 * Specifications for how content can be used can be add-ons to the content.
 * a.	But that can be removed or altered.
 * Must build some control mechanism into the content itself
 * a. E.g, DRM, watermark
 * b. But that breaks down the wall separating architecture & content
 * Cripple functionality to comply w/ law?
 * a. E.g., iTunes, Quality of Service
 * ii. This Principle will be addressed in Module 9e: Intellectual Property.
 * b. Understanding of digital library concepts is hampered by terminology.
 * i. One possible solution: Invent new terms
 * E.g., sharium, Information Commons, etc.
 * ii. Some terms persist: digital object, handle, metadata, etc.
 * iii. Hopefully this problem has diminished as DLs have become more common & familiar.
 * iv. One term is still ambiguous: DL.
 * c. The underlying architecture should be separate from the content stored in the library.
 * i. Separation of architecture & content
 * This is the premise of all markup languages: HTML, XML, etc.
 * HTML does this separation poorly.
 * ii. Functionality can be general to all content or specific to types of content.
 * E.g., text can be edited, images usually can only be viewed (except with special tools like PhotoShop); different file types invoke different applications, etc.
 * This is the function of modules in programming.
 * iii. “Characteristics that apply to all types of material”
 * Some characteristics are more or less universal: e.g., describable with the Dublin Core
 * iv. This Principle will be addressed in Module 4-b: Metadata
 * d. Names and identifiers are the basic building block for the digital library.
 * i. In the physical world:
 * e.g., [[w:Social_Security_number|SSN], house address, phone number
 * e.g., ISBN: not unique; gets reused
 * ii. Online:
 * URLs: Not unique, not persistent
 * DOI (http://www.doi.org) & PURL (http://purl.oclc.org): Unique & persistent
 * e. Digital library objects are more than collections of bits.
 * i. A stream of bits is what is downloaded.
 * But users interpret an intellectual object.
 * Can some of that interpretation be embedded into the structure of the bitstream?
 * ii. This becomes a more complex problem with complex objects.
 * f. The digital library object that is used is different from the stored object.
 * i. Architecture must distinguish between digital objects as they are:
 * created by an originator,
 * stored in a repository,
 * disseminated to a user.
 * ii. Legal ramifications: copying & caching
 * g. Repositories must look after the information they hold.
 * i. Archiving & long-term preservation
 * ii. Need DOIs / PURLs
 * iii. Migration to new formats
 * iv. Prevent hacking & unauthorized changes to files.
 * v. This Principle will be addressed in Module 8: Preservation
 * h. Users want intellectual works, not digital objects.
 * i. Complex objects are mutable.
 * ii. The same object can be part of multiple “works”.
 * E.g., an image as part of multiple documents.
 * E.g., the same paragraph or citation as part of multiple documents.

Topic: DSpace Architecture
Content based on http://www.dspace.org/index.php?option=com_content&task=view&id=145#overview This covers the popular DSpace system. Other related systems not covered include Greenstone and Fedora; these are similar to DSpace or the systems and architectures covered below. [| DSpace System Architeture]

 * 1. DSpace architecture overview
 * a. DSpace architecture has three layers and two APIs as shown in Figure 2.
 * i. Storage layer stores digital objects and their metadata in databases and file systems.
 * ii. Business logic layer includes key operations such as searching and browsing services. It also manages users and authorization;; it includes broad suites of services to access and preserve content.
 * iii. Application layer allows users to access DL system through its user interface. DSpace communicates with the outside world through this layer.
 * b. Each layer only invokes the layer below it. For example, the Application layer cannot access the Storage layer directly.
 * c. Each component in the Storage layer and the Business Logic layer has a defined API. Storage API (Public API) is a combination of APIs for components in the Storage Layer (Business Logic Layer).

 * 2. More details on components of the three-layers
 * d. Storage Layer
 * i. RDBMS: DSpace stores information about the user groups, organization and metadata of content, workflows, authorization, and indices.
 * ii. Bitstream Store: content is stored two ways - in the server's file system, or using the Storage Resource Broker (SRB), which is a robust storage manager with a backup feature.
 * e. Business Logic Layer
 * i. Search: it is based on the Lucene search engine.
 * ii. Browse: provides dates, authors, titles, and subjects.
 * iii. History recorder: it captures significant changes in DSpace.
 * iv. Administration toolkit: provides command line tool to create admins and configure DSpace system
 * v. Workflow system: it models item's status in the system such as submitted, step-1, step-2, archive, etc., so that people with different responsibilities can correct and view the item's status.
 * vi. Content management: it provides means to read or modify content in the storage layer.
 * vii. Core classes: are basic classes used throughout DSpace.
 * viii. Authorization system: it enforces policies, which are attached to resources. Policies also restrict responsibilities/actions of the users.
 * f. Application Layer
 * i. Web user interface: end-users access DSpace through the web-browser-based interface. It is the most used component in this layer.
 * ii. OAI-PMH data provider: it provides a platform for metadata harvesting.
 * iii. Item importer/exporter: the importer bypasses workflows assigned to a collection unless a flag is given specifically. The exporter can export a single item or a collection of items.
 * iv. Media filter: it converts content to another new form of content. For example, a thumbnail image can be created from an item containing an image by applying filters.
 * v. Registration: it is an alternate way to incorporate items, their metadata, and bit streams into DSpace.
 * vi. Sub-community management
 * vii. METS export tools (experimental): it exports DSpace items to a file system with the metadata in METS format

Topic: Federated Architecture - Networked Digital Library of Theses and Dissertations (NDLTD) with MARIAN as a mediation middleware

 * Content is based on: Gonçalves, Marcos A., Robert K. France, Edward A. Fox. 2001. MARIAN: Flexible Interoperability for Federated Digital Libraries, in Proceedings of the Fifth European Conference on Research and Advanced Technology for Digital Libraries (ECDL2001), Darmstadt, Germany, September 4-9, 2001, pp. 173-186 (http://www.dlib.vt.edu/reports/ecdl2001_8.pdf).
 * After several years, however, when OAI-PMH became more widely used, OCLC began to run a Union Catalog, harvesting from OAI data providers, and integrating that information with WorldCat records; VTLS and Scirus run services atop the Union Catalog at present.

 * 1. NDLTD overview
 * a. An international consortium of universities, libraries, and other institutions focused on electronic theses and dissertations.
 * b. A networked (federated) system that consists of multiple autonomous information systems (see the different collections in the bottom of Figure 3 such as VT OAI, MIT ETD, German PhyDis in member institutions), which are distributed in different locations and provide heterogeneous services.
 * c. Although the information is searched and retrieved from various member institutions, a unified and transparent view of information sources is provided to DL patrons.
 * d. Characteristics that complicate interoperability across member systems
 * i. Autonomy: member institutions manage most of their services for their scholars (e.g., the Virginia Tech library administers its ETD collection mostly for its own patrons, but at the same time participates in NDLTD).
 * ii. Decentralization: member institutions are not asked to report updates on their data to a central coordinator.
 * iii. Minimal interoperability: members should provide Unique Resource Names (URNs) and metadata records for all data but are not required to support the same standards/protocols.
 * iv. Heterogeneity: member institutions might use different languages, metadata standards, protocols, and character codings; they differ in user characteristics, preferences, and capabilities. This is one of the big challenges in NDLTD.
 * v. Massive amount of data and dynamism: new member institutions are constantly added and they provide input data continuously.

 * 2. Union Archive vs. Federated Search: design decisions for federated architecture
 * a. Union Archive
 * i. Information is periodically collected from each member institution
 * ii. Processed and merged with information from other institutions
 * iii. Loaded into the central union archive
 * iv. User queries are searched within the union archive without interacting with individual member institutions
 * v. ADVANTAGES
 * Adequate performance at query time
 * vi. DISADVANTAGES
 * Information might not be up-to-date (unless information collection period is short)
 * Concerns about data quality (multiplicity of representation, errors in data, imprecision) and consistency
 * b. Federated Search
 * i. There is no central archive. Data stays in each member institution.
 * ii. User entered queries are passed to each member institution at query time.
 * iii. ADVANTAGES
 * It is guaranteed to retrieve up-to-date information.
 * There is no data replication (whereas the union archive contains copies of original information from member institutions).
 * iv. DISADVANTAGES
 * More sophisticated strategies for query optimization and data fusion (of retrieved information from each member institutions) are needed.
 * Low performance compared to union archive approach
 * v. Other considerations
 * Network availability, latency, amount of data to transfer, etc. should be considered (e.g., some member institutions might have low network availability. This worse-case situation decides the overall performance of the federated DL system).
 * c. Union Archive approach is used in NDLTD due to:
 * i. Complexity of query translation in heterogeneous environment (e.g., different languages, protocols, etc.)
 * ii. Poor and inconsistent network connectivity in some member institutions
 * iii. Variability in server load and administration.

 * 3. NDLTD Union Archive Architecture
 * a. The MARIAN Mediation Middleware acts as a tool supporting interoperability. It provides NDLTD users a uniform interface to search and browse collections in member institutions, which use different protocols, formats, and systems.
 * b. Like other union archive approaches, it has mechanisms to:
 * i.Harvest data from various sources
 * To overcome the differences in member institution systems, special software modules such as wrappers (shown in Figure 3) are used.
 * To apply those wrappers, more information about the data collections, such as capabilities of remote collections and their internal document structures, should be known to the NDLTD system.
 * 5SL language can describe collection specific information and it is used to semi-automatically generate wrappers (see 5SL Source Description and Wrapper Generator in Figure 3).
 * ii. Combine (fuse) those harvested data for use (shown in Figure 4)
 * Each metadata standard has different classes such as Subject, Individual, Headings, Keywords, etc.
 * Merge those classes that have similar semantics (meanings); separate them if they have different semantics.
 * This approach is an attempt to reduce redundancy of data while keeping the collected data flexible enough to be modified in changing circumstances.

Topic: A Service-Oriented Architecture (SOA) for CiteSeer

 * Content is based on: Petinot, Y., Giles, C. L., Bhatnagar, V., Teregowda, P. B., Han, H., and Councill, I. 2004. A service-oriented architecture for digital libraries. In Proceedings of the 2nd international Conference on Service Oriented Computing (New York, NY, USA, November 15 - 19, 2004). ICSOC '04. ACM, New York, NY, 263-268. DOI= http://doi.acm.org/10.1145/1035167.1035205
 * 1. Current CiteSeer architecture overview
 * a. CiteSeer (http://citeseer.ist.psu.edu/) is a scientific literature digital library and search engine that provides citations and cached papers in the fields of computer science and information science.
 * b. It consists of three basic components
 * i. A focused crawler
 * ii. Document archive and related indices
 * iii. Query interface
 * c. How it works
 * i. By a focused crawler, raw documents in PDF and PostScript formats are collected into a File System Document Repository.
 * ii. After filtration of academic documents, data such as citations, full-text and metadata are extracted from them using autonomous citation indexing and stored into relevant indices and databases. References in research papers are linked to each other for providing navigation and evaluation services.
 * iii. Through a web application, users can search the index containers and databases.
 * iv. Lock Server, which is located between the Full-Text Index container and Full-Text DB, is used to lock the table or index level during updates.

 * 2. New CiteSeer architecture based on SOA
 * a. Current CiteSeer architecture in Figure 5 might be seen as a monolithic system architecture, where several elementary services such as indexing, filtering, citation extracting, citation ranking are coordinating with each other to achieve tasks.
 * b. We might think of those services as Web Services and re-organize the architecture around them.
 * c. Web Services in the new architecture can be categorized into two parts with an additional service, a UDDI registry service, where all the Web Services are registered.
 * i. Part 1 - Fundamental CiteSeer services
 * Citation Extraction Service: it provides autonomous citation parsing functionality.
 * Citation Graph Service: it maintains a citation graph, which is a directed graph where nodes represent documents and edges represent citation relationships, for example, cites/cited-by relationships.
 * ii. Part 2 - Utility services in most information systems
 * Indexing Service: It provides functionality such as inverted file and mapping elementary tokens to documents. In CiteSeer, two different kinds are used independently to index documents and their citations.
 * Metadata Service: It is equivalent to providing the OAI-PMH service.
 * Electronic Repository Service: It is aware of duplicate documents. Federation of this service might be provided as a solution for copyright management and mirroring concerns.
 * Electronic Conversion Service: It converts an electronic format to another. If the other format conversion services are made available on the Internet, CiteSeer can support those conversion services immediately.
 * Duplicate Identification Service: It compares the similarity between two documents to check the amount of overlap. This service might be used to discover an alternate URI.
 * iii. Service Registration (UDDI registry service)
 * CiteSeer Web Services can be used by Semantic Web agents without problems.
 * However, for human users to access those Web Services through the Web application and CiteSeer Middleware, a meeting point, where Web Services are advertised and discovered, is necessary.
 * The UDDI registry Web Service does this job.
 * d. To transform Web Services into Semantic Web Services, Ontology Web Language for Services (OWL-S) is used to express the Web Service processes.
 * e. In summary, Semantic Web agents have access to individual Web Services expressed by OWL-S and the human users also have access to those through the Web Application layer and Middleware layer that has access to the UDDI registry Web Service.

Topic: Component-based DL architecture (e.g., Open Digital Libraries)

 * The first clear argument to shift to components for DLs was developed during the doctoral research of Hussein Suleman. The most complete reference is his dissertation: Hussein Suleman, "Open Digital Libraries", Nov. 2002, Virginia Tech Computer Science PhD dissertation, Blacksburg, VA, USA, http://scholar.lib.vt.edu/theses/available/etd-11222002-155624/

 * Components can be connected together so a DL can be constructed from modules. Figure 7 shows how an Open Digital Library (ODL) can connect users (see left) with content collections (see right), building upon OAI-PMH. Note that this work coincided with work on MARIAN but pre-dates the development of SOA, as explained above in connection with CiteSeer. The right side shows a relatively standard application of OAI-PMH to get to the metadata, and thence the data.  The center shows the modules. The left shows that one or more of the modules connects with the users.

 * In the middle, we see modules connected with XPMH. Suleman defined an extension of OAI-PMH and called it XPMH.  It allowed modules to get input from other modules in similar fashion to OAI harvesting, and to provide output that could be used by other modules through a type of OAI data providing.

 * Some of the modules included: Filter, ODLUnion, ODLSearch, ODLBrowse, and ODLRecent. The DL-in-a-box project made these available, so DL architects could connect these key pieces of a DL together, along with other modules, to build a tailored system, such as under control of 5SGen (5S-based generator - see Rohit Dilip Kelapure, "Scenario-Based Generation of Digital Library Services", June 2003, Virginia Tech Computer Science MS thesis, Blacksburg, VA, USA, http://scholar.lib.vt.edu/theses/available/etd-06182003-055012/). The WS-ODL framework (see Roberto et al., in Resources), extended and updated ODL.

Resources

 * 1. Principles of DL architecture
 * a Readings for students
 * i. Arms, W. Y. (1995). Key Concepts in the Architecture of the Digital Library. D-Lib Magazine, 1(1). http://dx.doi.org/cnri.dlib/july95-arms
 * ii. Kahn, R., & Wilensky, R. (1995). A Framework for Distributed Digital Object Services. http://dx.doi.org/cnri.dlib/tn95-01

 * 2. Federated (networked) architecture
 * a Readings for students
 * i. Marcos André Gonçalves, Robert K. France, and Edward A. Fox. "MARIAN: Flexible Interoperability for Federated Digital Libraries." Research and Advanced Technology for Digital Libraries: [Proc. of] 5th European Conference, ECDL-01 (Darmstadt, Germany: 4-9 Sept. 2001) Springer, 2001, pp. 173-186. http://www.dlib.vt.edu/reports/ecdl2001_8.pdf

 * 3. Distributed architecture
 * a. Readings for students
 * i. Rodger J. McNab, Ian H. Witten, Stefan J. Boddie, "A Distributed Digital Library Architecture Incorporating Different Index Styles (1997)," Advances in Digital Libraries. (Discusses MG and MR, related to the Greenstone system.)  URL: http://www.cs.waikato.ac.nz/~ihw/papers/RM-IHW-SB-Adistributeddl.pdf

 * 4. Service Oriented Architecture (SOA)
 * a. Readings for students
 * i. Yves Petinot, C. Lee Giles, V. Bhatnagar, Pradeep B. Teregowda, Hui  Han, Isaac G. Councill, "A Service-Oriented Architecture for Digital Libraries (2004)," (related to CiteSeer) at http://clgiles.ist.psu.edu/papers/ICSOS-2004-service-oriented-arch.pdf

 * 5. (Optional) Component-based DL architecture: Open Digital Libraries (ODL)
 * a. Reading for students
 * i. Hussein Suleman and Edward A. Fox (2001), A Framework for Building Open Digital Libraries, D-Lib Magazine, Volume 7 Number 12 at http://www.dlib.org/dlib/december01/suleman/12suleman.html
 * b. More resources for students (optional) and instructors
 * i. Virginia Tech's Open Digital Libraries project page, which contains project description, publications, tools, components and protocols and other resources of the component-based DL architecture. URL: http://www.dlib.vt.edu/projects/OAI/
 * ii. (WS-ODL: Overcoming ODL's limitations) Pablo A. Roberto et al., "A Web Services-Based Framework and a Wizard Tool for Building Componentized Digital Libraries" at http://www.lbd.dcc.ufmg.br:8080/colecoes/sbbd/2006/007.pdf

 * 6. (Optional) Readings for other architectures
 * a. William P. Birmingham (1995), "An Agent-Based Architecture for Digital Libraries," D-Lib Magazine article (emerging from the University of Michigan DLI-1 project) at http://www.dlib.org/dlib/July95/07birmingham.html
 * b. Carl Lagoze, Sandy Payette, Edwin Shin, Chris Wilper (2005), "Fedora: An Architecture for Complex Objects and their Relationships," Journal of Digital Libraries, Special Issue on Complex Objects, 6(2): 124-138. DOI: 10.1007/s00799-005-0130-3. Preprint available at http://arxiv.org/abs/cs.DL/0501012
 * c. "NSDL Library Architecture: An overview" (2005) at http://onramp.nsdl.org/eserv.php?pid=onramp:19&dsID=nsdl_arch_overview.pdf
 * d. Xiaoming Liu, et al. (2002), "A Scalable Architecture for Harvest-Based Digital Libraries: The ODU/Southhampton Experiments," D-Lib Magazine 8(11) article at http://www.dlib.org/dlib/november02/liu/11liu.html

Concept map

 * (created by students)
 * Note: IHMC Cmap Tools is an open source client tool to create concept maps. CmapServer enables the users to collaborate and share concept maps anywhere on the internet.  Both software can be downloaded freely for educational purposes from http://cmap.ihmc.us/download/index.php

Exercises / Learning activities

 * a. Students form groups
 * b. A specific DL architecture is assigned to each group
 * c. Each group presents a DL architecture overview with its design ideas (in which situations the architecture is most appropriate), advantages, disadvantages, etc.

 * 1. Group analysis of individual architectures
 * Prior to the class session, organize the students into groups. Each group will be assigned to investigate/analyze one of the architectures listed above:
 * a. Federated architecture
 * b. Distributed architecture
 * c. Service-oriented architecture
 * d. (Optional) Architecture not mentioned in the lecture such as Component-based DL architecture, peer-to-peer-based DL architecture, etc.
 * Each group will be expected to read more than just the assigned class readings, in order to fully understand the assigned architecture. At the next class period, each group will give presentation about an overview of what it has learned about the situations in which the architecture is most appropriate, its advantages and disadvantages, etc.
 * [Note for instructor: Rather than lecturing about the architecture, this learning activity could be expanded, so that the students are presenting the primary material. If that approach is taken, then the instructor should be prepared to fill in the gaps or correct any misstatements made in student group presentations.]

Evaluation of learning outcomes

 * The group presentations described in section 12 could be graded to evaluate students' learning
 * Group presentations might be evaluated in terms of their comprehensiveness (did they include the important features and characteristics of the architecture?), their clarity (did they explain the architecture in a way that it could be distinguished from the other architectures?), and the quality of the presentation (e.g., slide quality, presentation style, use of time, and Q/A session).

Glossary

 * 1. Universal Description, Discovery and Integration (UDDI) is a platform-independent, XML-based registry for businesses worldwide to list them on the Internet. UDDI is an open industry initiative, sponsored by OASIS, enabling businesses to publish service listings and discover each other and define how the services or software applications interact over the Internet.
 * 2. DC: The Dublin Core metadata element set is a standard for cross-domain information resource description. It provides a simple and standardized set of conventions for describing things online in ways that make them easier to find. The Dublin Core is widely used to describe digital materials such as video, sound, image, text, and composite media like web pages. Implementations of the Dublin Core typically make use of XML and can be Resource Description Framework based. The Dublin Core is defined by NISO Standard Z39.85-2007. (Based on excerpt from wikipedia.org)
 * 3. OAI-PMH (Open Archives Initiative Protocol for Metadata Harvesting) is a protocol developed by the Open Archives Initiative. It is used to harvest (or collect) the metadata descriptions of the records in an archive so that services can be built using metadata from many archives.
 * 4. Service Oriented Architecture (SOA) is a paradigm for organizing and utilizing distributed capabilities that may be under the control of different ownership domains. It provides a uniform means to offer, discover, interact with, and use capabilities to produce desired effects consistent with measurable preconditions and expectations.
 * 5. SOAP (Service Oriented Architecture Protocol) is a protocol for exchanging XML-based messages over computer networks, normally using HTTP/HTTPS. SOAP forms the foundation layer of the Web services stack, providing a basic messaging framework that more abstract layers can build on.
 * 6. Web Services have measurable preconditions and expectations.
 * 7. Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies, and is endorsed by the World Wide Web Consortium. OWL is considered one of the fundamental technologies underpinning the Semantic Web, and has attracted both academic and commercial interest. (Excerpt from wikipedia.org)
 * 8. OWL-S is a simplified ontology scheme, within the OWL-based framework of the Semantic Web, for describing Semantic Web Services. It will enable users and software agents to automatically discover, invoke, compose, and monitor Web resources offering services, under specified constraints (Excerpt from W3C at http://www.w3.org/Submission/OWL-S/)

Additional useful links

 * Interactive demo
 * a. Distributed Digital Library of Mathematical Monographs at http://mathbooks.library.cornell.edu:8085/Dienst/UIMATH/2.0/Search
 * b. European Digital Library (example of federated system) at http://www.edlproject.eu/

Contributors

 * a. Development
 * i. Seungwon Yang (Virginia Tech)
 * ii. Dr. Edward A. Fox (Virginia Tech)

 * b. Evaluation
 * i. Liz Liddy (Syracuse University)
 * ii. Jerome McDonough (University of Illinois at Urbana-Champaign)
 * iii. Ingeborg Solvberg (Norwegian University of Science and Technology-NTNU)
 * iv. Project members at the University of North Carolina at Chapel Hill provided additional comments.

title: Digital Libraries/Architecture overview