“Despite mans ability to generate information he is limited in his ability to link the information he generates to the information he needs in his daily conflicts. his strivings and aspirations, his welfare and, in a very direct way, his humanity. Indeed, if he were to bridge the gap between the generation and utilization of information, the horizon would be more promising in terms of his ability to reduce injustice and to provide a medium for constructive human development and enterprise.”
Anthony Debons 1974
Introduction
Scientific activity generates and uses a massive volume of many kinds of digital information: raw data, analyzed data, simulations, notes, letters, reports as well as the more traditional published journal articles. Through the World Wide Web and URLs, scientific information has become a rich web of connected digital information. However, as McGrath, Futrelle, and Plante (1999: 2) point out ‘there remains a significant and lasting challenge for humans to exploit this richness, to discover, access, and understand the knowledge that may reside or be created from digital resources.’ This essay examines advances in digital technology that might enable scientists to overcome some of these challenges and provide the ‘Linked Open Science’ (LOS) called for by Kauppinen and Mira de Espindola (2011) that is needed to tackle some of the greatest problems of our time.
Using the internet to publish information in accessible ways: the semantic web
Linked Open Science (LOS) an approach that ‘interconnects scientific assets to enable transparent, reproducible and transdisciplinary research.’ (Kauppinen:2011) Can only be achieved through publishing data using semantic web technology. But what is the semantic web? The original concept was first introduced by the web's inventor Tim Berners-Lee in the nineteen-nineties. Since then it has attracted a lot of excited attention and some outlandish promises have been made for it. Semantic web technologies, we are told, will provide computers with the ability to perform abstract cognitive processes previously the preserve of human beings. The literature doesn't shy from referring to computers that can 'understand' and 'reason' (Byrne&Goddard 2010) 'manipulate meaningfully', 'choose', 'infer' and 'comprehend' (Berners-Lee et al 2001). In addition to the hype, the sheer number of different approaches to the semantic web also muddies the water. Each new application developed emphasises a different feature of the technology so there are allot of competing definitions. Wikipedia's entry on the semantic web had no less than
1,701 edits at time of writing. In order to avoid vacuous hyperbole and cut a channel through the multitude of competing versions this essay will focus on what is perhaps one of the most conservative and hence realisable definitions of the semantic web, that of the World Wide Web Consortium (W3C), the international web standards committee founded in 1994 by Berners-Lee.
For the W3C the semantic web is first and foremost the 'web of data'. By data they refer to the raw information that populates governmental databases, personal bank statements, and scientific reports. And by web they refer to its essential interconnectedness. Although the web of data builds upon and evolves the extant web of documents it also contrasts quite markedly. It relies upon two essential innovations. First, the introduction of a common format for data. Currently data is stored in a variety of different formats, by different databases and computer programs. A common format would allow data pulled from radically different sources to be 'integrated' and 'combined' in interesting and productive ways. The second innovation is the provision of a language for enabling data to relate to actual-world-things. Such a language would enable users to discover and use databases and information resources on the basis that they contain data pertaining to one self-same thing. The term 'thing' is being used here in a very broad way, it might refer to a person, a city, an historical date, a protein or an object in the traditional sense like a IKEA book shelf, essentially anything that there can be published data on is a thing in the semantic web. (Ref: W3C 2001) It’s no wonder then that science is one of the leading areas developing semantic web technology. (Berners-Lee: 2009) It has allot to gain, not least an efficient and standardised means to distribute scientific data globally via the internet. We now need to take a closer look at semantic web technology.
Identifying appropriate and innovative methods of digital data representation and organisation: RDF, RDFS and OWL
Semantic web technology rests on three pillars: RDF, RDFS and OWL. In this section we’ll take a look at each of them in turn in relation to the goal of a truly LOS. Resource Description Framework (RDF) is the common format that really founds semantic web technology, it is a W3C standard for web meta-data or, in other words, a set of rules for providing simple descriptions of webbed data – the title, author, modification date and so on. The very term ‘resource’ suggests a greater generality than the traditional term web page, this is intended, data described in this way need not be formatted for the web and can be accessed and used by applications different to one it is intended for. RDF is based upon the idea that things have properties and these properties can be described by making statements about them, such statements are structured in triples consisting of subject, object and predicate. In the example statement: the web page http://www.example.com/fictional.html was created by Tom Barker, the web page is the subject about which something is said, the predicate is the property or the relation of the subject, in this case it having been ‘created by’ someone and the value of the property is the object, Tom Barker. RDF formalises such statements to make them ‘machine-readable’ by using Universal Resource Identifiers (URI). Unlike URLs URIs can pertain to anything that a RDF statement may need to refer to. So the person Tom Barker will have a URI so to would the abstract concept of ‘creation’ as well as the web page itself. It is important to note that although the URIs are expressed as a URL they needn’t refer to actual pages on the web, they are simply a unique identifier. Our example above could be presented in a RDF statement thus:
Subject: http://www.example.com/fictional.html
Predicate: http://purl.org/dc/elements/1.1/creator
Object: http://www.somegreatorganisation.com/futureemployee.html
The most common implementation language of RDF is XML:
This example is simple but RDF graphs can be more complicated with more predicates and objects related to the subject. (Ref: W3C 2004) An LOS graph would include all scientific researchers, research institutions, publications, and data sets to be linked in this simple way. A large part of the work that lies ahead in LOS is designing these complex graphs and building these webs of linked scientific data.
As we saw RDF is a standard for the syntax of descriptive sentences pertaining to things, their properties and relations; it is not a vocabulary of descriptive terms. Where RDF provides the grammar, it is RDF Schemas (RDFS) that provide the words. RDFS can be defined as technical vocabularies or taxonomies developed by users to describe the types of things their statements refer to. The resources schemas are a formal hierarchy consisting of ‘resources’ (in the semantic web every thing is a resource), types of resources or ‘classes’ (e.g. Research Institution) and these are broken down again into single ‘instances’ (e.g. City University London) (Ref: W3C 2004). This idea is taken a step further with Web Ontology Language (OWL). OWL includes the taxonomy of RDFS, that is the descriptive terms of classes of things and their relations, together with a set of ‘axioms’ about the computational operations that can or cannot be conducted on those things. There are a number of extant ontologies we could use to deliver LOS.
• NASA’s Semantic Web for Earth and Environmental Terminology (NASA 2011)
• An Ontology for Engineering Mathematics (Gruber&Olsen 1994)
• The Open Biological and Biomedical Ontologies (OBO 2012)
Other ontologies are urgently required to cover the entirety of scientific effort and deliver LOS.
Utilizing recent advances in information and communications technology to support completion of a wide range of information related tasks: LOS and the semantic web
As Bechhofer et al (2011: 1) point out the “simple move from paper-based to electronic publication does not necessarily make a scientific output decomposable. Nor does it guarantee that outputs, results or methods are reusable.” In this section we will look at the ways that scientists might wish to reuse scientific output and how semantic web technology can enable this.
The first reuse is validation. Integral to any scientific discovery is peer review, colleagues working in the field need to critically assess research data and methodology before committing to the research conclusions. A digitally published scientific paper structured according to RDF, RDFS & OWL standards could be linked as a subject to the following objects – original research data, research methodology, context notes, and all other studies of the same subject. This would greatly reduce the time consumed in acquiring this data as the reviewer could access it by clicking on a link rather than by making a formal request to the originating colleague and their research institution. Ultimately it will be possible to analyse semantic and statistical similarities in linked data-sets automatically to detect plagiarism and copyright issues. (Ref: Kauppinen et al 2011)
The second reuse is in planning new research. A scientist has been given funding to perform some research into sleep deprivation; she is planning her research and wants to know what other studies have been done into sleep deprivation, what data they generated and how it was analysed. In a fully linked open science semantic web technology would be able to locate all this very simply and accurately. A software agent would send out a request for the URI attached to scientific studies of sleep deprivation. The first search would look for instances where that URI was the principal subject, later the search could extend to include the same URI as an object or predicate. Information retrieval is more accurate with semantic web technology
The third reuse is in research itself. Here’s another hypothetical scenario: a climate science researcher requires geographical information data sets to use in a paper she is putting together on climate change in north east India. These data sets exist and are structured according to the standards of the semantic web and are accordingly easy to find. This significant innovation means that she can simply link to these data sets rather than downloading them to her local hard drive and thus ease pressure on local memory. Open Provenance Model Vocabulary (Zhao: 2010) ascribes important provenance meta-data to data-sets like the one in our example. Our researcher could find out who created the geographical dataset, who published it, who has transformed it, and even who else has used it.
Conclusion
Semantic web technology makes science more efficient. Although it is only one part in delivering Linked Open Science, it is perhaps the most important part. The technology and standards are now in place, however there now remains lots of work to be done converting existing scientific data into the RDF format, building scientific RDFSs and OWLs. Information specialists have an important role to play in this work.
Bibliography
Beckett, Dave (2005) Dave Beckett’s Resource Description Framework (RDF) Resource Guide [online] Available at RDF http://planetrdf.com/guide/ [accessed 02/01/2011]
Bechhofera, Sean et al (2011) Why Linked Data is Not Enough for Scientists, Preprint submitted to Elsevere [online] available at http://users.ox.ac.uk/~oerc0033/preprints/research-objects.pdf [accessed 07/01/2012]
Berners_lee, Tim, Hendler, James, and Lssila, Ora (2001) The Semantic Web Scientific American 284 34-43 [online] Available at: www.sciam.com/article.cfm?id=the-semantic-web. [accessed 02/01/2012]
Berners-Lee, Tim (2009) Tim Berners-Lee On The Next Web TED [online] Available at: http://www.ted.com/talks/tim_berners_lee_on_the_next_web.html [accessed 05/01/2011]
Berners-Lee, Tim (2011) Sir Tim Berners-Lee on Open Data [online] Available at: http://www.youtube.com/watch?v=ppRzJW0FDwk [accessed 05/01/2012]
Berners-Lee, Tim (2010) Open Linked Data For a Global Community [online] Available at: http://www.youtube.com/watch?v=ga1aSJXCFe0 [accessed 05/01/2012]
Bryne, Gillian & Goddard, Lisa (2010) The Strongest Link: Libraries and Linked Data, D Lib magazine
Floridi, Luciano (2011) Web 2.0 vs. The Semantic Web: A Philosophical Assessment [online] Available at: http://www.philosophyofinformation.net/publications/pdf/w2vsw.pdf [accessed 27/12/2011]
Gruber, Thomas R. and Olsen, Gregory R (1994) An Ontology for Engineering Mathematics [online] Available at: http://www-ksl.stanford.edu/knowledge-sharing/papers/engmath.html[accessed 07/01/2012]
JISC (2010) ACRID: Advanced Climate Research Infrastructure for Data {online] Available at: http://www.jisc.ac.uk/whatwedo/programmes/mrd/clip/acrid.aspx [accessed 07/01/2012]
Kauppinen, Tomi (2010) About (Linked Open Science) [online] Available at; http://linkedscience.org/about/ [Accessed on 06/01/2012]
Kauppinen, Tomi, Mira de Espindola, Giovanna (2011) Linked Open Science—Communicating, Sharing and Evaluating Data, Methods and Results for Executable Papers [online] Available at: http://kauppinen.net/tomi/linked-open-science-camera-ready-2011-03-28.pdf [accessed 05/01/2012]
McGrath, Robert E. Futrelle, Joe, Plante Ray (1999 ) Digital Library Technology for Locating and Accessing Scientific Data [online] Available at: http://arxiv.org/PS_cache/cs/pdf/9902/9902012v1.pdf
[Accessed on 06/01/2012]
NASA (2011) Semantic Web for Earth and Environmental Terminology [online] Available at: http://sweet.jpl.nasa.gov/sweet/ [accessed 07/01/2012]
OBO (2012) The Open Biological and Biomedical Ontologies [online] Available at: http://open-biomed.sourceforge.net/opmv/ns.html [accessed 07/01/2012]
W3C (2011) W3C Semantic Web Activity [online] Available at: http://www.w3.org/2001/sw/
[accessed 01/01/2012]
W3C (2004) World Wide Web Consortium Issues RDF and OWL Recommendations [online] Available at: http://www.w3.org/2004/01/sws-pressrelease [accessed 02/01/2012]
W3C (2004) Resource Description Framework RDF[online] Available at: http://www.w3.org/RDF/ [accessed 02/01/2012]
W3C (2004) RDF Primer [online] Available at: http://www.w3.org/TR/2004/REC-rdf-primer-20040210/ [accessed 02/01/2012]
W3C (2004) RDF Vocabulary Description Language 1.0: RDF Schema [online] Available at: http://www.w3.org/TR/rdf-schema/ [accessed 04/01/2012]
Zhao, Jun (2010) Open Provenance Model Vocabulary Specification [online]
Available at: http://open-biomed.sourceforge.net/opmv/ns.html [accessed 07/01/2012]
08/01/2012
31/10/2011
Assignment 1 DITA
http://unquietcity.blogspot.com/2011/10/assignment-1-dita.html
Phonographic arts collective UNDRFM require a means of organising and accessing data pertaining to their member’s and their member's web-published works. This essay will critically evaluate and describe the processes and technologies involved in managing data of this nature.
There are two key approaches to managing data - database and file - both involve structuring data and facilitating access, however there are some fundamental differences and, in a number of ways, the database approach can be seen as solving some of the problems associated with the file system. The first significant difference is that the file system involves differentiated data and the database integrated data. This simply means that where a different filing system exists for each different department of an organisation the database system collects and centralises all the data of a given organisation. This may seem of little import to a small organisation like UNDRFM however it has an important consequence, namely that data is more secure when stored within a database because access to it can be controlled by a central administrator. The second major difference, which stems from the first, is that the database involves independent data and the file system dependent data. In its simplest formulation this means that where the code or structuring logic for locating data in a database is not known by the user or application searching for the data it is absolutely essential that it is known when searching a file system, or in other words, database data contains meta-data pertaining to the its location within the database and filed data does not. This gives the database greater flexibility which is useful to this project for two obvious reasons: it enables us to provide access to a large number of users without having to share the code or structuring logic of the files system and it allows us to modify and change the database structure without having to alter the coding of programs accessing it.
The database approach with its improved security, flexibility and program independence is the most suitable data management system to use. The most common type of database is the relational database the basic elements of which are entities and relations. An entity is a thing that is represented and described by the data and a relation is a relationship that exists between two or more entities. For us the two entities involved are: a) members and b) web-sites. The relation that exists between them is: members work is published on a website. The design of a database begins by mapping the fluid structure that will house the data, that is, by sketching the entities and their possible relations in an ER scheme. The ER scheme provides the blueprint from which databases are built.
SQL (Standard Query Language) is the language used to communicate with databases. The UNDRFM members database will be created, populated and searched using SQL. For example:
Create table Members
(Name primary key char [50],
E mail address char [50],
Home city char [25],
Published on char [10];
In order to fully populate the “Website” data table it is necessary to input the URLs of phonography websites, this information will have to retrieved. There are three perspectives from which to analyse information retrieval. Firstly there is the user who possess an information need. In this case UNDRFM need the URLs of phonography web sites. A query that can be defined in Broder's taxonomy as a 'navigational query' as its intention is the home page of an organisation e.g. the London Sound Survey. Secondly there is the system that is used to satisfy this information need. This term refers to the software and hardware that is used to store, locate and process the required information. In this instance the system view broadly covers the internet, WWW and HTML. The Internet: is the vast network of networks connecting innumerable computers via electronic, wireless, and fibre-optic connections into one massive super-network. The internet is the infrastructure and the WWW is one service that uses it - it is a system of web pages connected by hypertext links. One either follows a link or types in a Universal Resource Locator (URL) address. The computer, via the web browser and web server, finds and gets the corresponding page from its networked host. And finally the last important component of our systems view is Hyper Text Mark Up Language (html) which Describes the content of web pages. It's not a programming language it is a mark up language that consists of mark up tags that usually come in pairs: a start tag and an end tag that are in <> brackets. The third and final perspective from which to view information retrieval is that of the source. This view covers the providers of the information and in our example includes the Sonic Arts Network.
We will be performing a key word search using the index terms field recording. A Google exact match search on the terms “field recording” provided an inverted file of around 2,330,000 web pages in 0.17 seconds. From this we will use a browsing technique to locate the URL of field recording publishing sites. This is involves using hyper text - the text that appears on a web page that contains links (hyperlinks) to other documents on the web that are accessible by clicking the hypertext - to navigate from one field recording website to another. If the keyword search failed to yield sufficient results we could modify the search query in two ways 1) by searching the synonym: “phonography” or 2) by trimming the words to their root e.g. “sound record” and “phonograph”. There are two ways of evaluating our search - qualitatively or quantitatively. For this project we will conduct a qualitative analysis of the search's efficacy from the perspective of the client. This will take the form of a questionnaire sent out to UNDRFM members that simply asks if the results of the search were useful to its members.
When searching unstructured information using the retrieval methods discussed above the results are probabilistic – the web pages displayed 'probably' meet the needs of the user. The searches that users of the UNDRFM database perform are by contrast deterministic, that is, they definitely meet the needs of the user. They are very precise searches for information you know is there because it is your information and it is structured. IR uses natural language and Database searches use SQL:
The command: Select name from members; will produce a result that details all the members names.
Select organisation from websites where web id = 1; will display the website with the id 1 – London Sound Survey.
Select name, url
From members, websites
where published on = 1
and published on = web id;
Will display all the names of people who've work published on London Sound Survey's web site as well as the site's URL.
The grammar is very strict. Unlike natural language where if you err you may still be understood, the smallest mistake in the syntax of an SQL instruction means the computer will fail to read and execute the command. This is a problem with Databases in particular and web 1.0 technology in general – they require the developer to become a polyglot.
Bibliography
Macfarlane, A., Butterworth, R., Dykes, J., (2009) The Internet and the World Wide Web, London: City University
Macfarlane, A., Butterworth, R., Krause, A., (2009) Structuring and Querying Information Stored in Databases, London: City University
Macfarlane, A. (2009) Information Retrieval, London: City University
Musciano, C., & Kennedey, B., (2002) HTML & XHTML The Definitive Guide 5th Edition, Sebastopol CA: O'Reilly & Assoc.
Robertson, S.E., & Sparck Jones, K., (1997) Simple, Proven Approaches To Text Retrieval, London: City University.
Taylor, A G., (2010) SQL For Dummies 7th Edition, Hoboken NJ: Wiley Publishing INC.
SQL Course [online] Available http://www.sqlcourse.com/index.html
Search SQL Server [online] Available http://searchsqlserver.techtarget.com/
There are two key approaches to managing data - database and file - both involve structuring data and facilitating access, however there are some fundamental differences and, in a number of ways, the database approach can be seen as solving some of the problems associated with the file system. The first significant difference is that the file system involves differentiated data and the database integrated data. This simply means that where a different filing system exists for each different department of an organisation the database system collects and centralises all the data of a given organisation. This may seem of little import to a small organisation like UNDRFM however it has an important consequence, namely that data is more secure when stored within a database because access to it can be controlled by a central administrator. The second major difference, which stems from the first, is that the database involves independent data and the file system dependent data. In its simplest formulation this means that where the code or structuring logic for locating data in a database is not known by the user or application searching for the data it is absolutely essential that it is known when searching a file system, or in other words, database data contains meta-data pertaining to the its location within the database and filed data does not. This gives the database greater flexibility which is useful to this project for two obvious reasons: it enables us to provide access to a large number of users without having to share the code or structuring logic of the files system and it allows us to modify and change the database structure without having to alter the coding of programs accessing it.
The database approach with its improved security, flexibility and program independence is the most suitable data management system to use. The most common type of database is the relational database the basic elements of which are entities and relations. An entity is a thing that is represented and described by the data and a relation is a relationship that exists between two or more entities. For us the two entities involved are: a) members and b) web-sites. The relation that exists between them is: members work is published on a website. The design of a database begins by mapping the fluid structure that will house the data, that is, by sketching the entities and their possible relations in an ER scheme. The ER scheme provides the blueprint from which databases are built.
SQL (Standard Query Language) is the language used to communicate with databases. The UNDRFM members database will be created, populated and searched using SQL. For example:
Create table Members
(Name primary key char [50],
E mail address char [50],
Home city char [25],
Published on char [10];
In order to fully populate the “Website” data table it is necessary to input the URLs of phonography websites, this information will have to retrieved. There are three perspectives from which to analyse information retrieval. Firstly there is the user who possess an information need. In this case UNDRFM need the URLs of phonography web sites. A query that can be defined in Broder's taxonomy as a 'navigational query' as its intention is the home page of an organisation e.g. the London Sound Survey. Secondly there is the system that is used to satisfy this information need. This term refers to the software and hardware that is used to store, locate and process the required information. In this instance the system view broadly covers the internet, WWW and HTML. The Internet: is the vast network of networks connecting innumerable computers via electronic, wireless, and fibre-optic connections into one massive super-network. The internet is the infrastructure and the WWW is one service that uses it - it is a system of web pages connected by hypertext links. One either follows a link or types in a Universal Resource Locator (URL) address. The computer, via the web browser and web server, finds and gets the corresponding page from its networked host. And finally the last important component of our systems view is Hyper Text Mark Up Language (html) which Describes the content of web pages. It's not a programming language it is a mark up language that consists of mark up tags that usually come in pairs: a start tag and an end tag that are in <> brackets. The third and final perspective from which to view information retrieval is that of the source. This view covers the providers of the information and in our example includes the Sonic Arts Network.
We will be performing a key word search using the index terms field recording. A Google exact match search on the terms “field recording” provided an inverted file of around 2,330,000 web pages in 0.17 seconds. From this we will use a browsing technique to locate the URL of field recording publishing sites. This is involves using hyper text - the text that appears on a web page that contains links (hyperlinks) to other documents on the web that are accessible by clicking the hypertext - to navigate from one field recording website to another. If the keyword search failed to yield sufficient results we could modify the search query in two ways 1) by searching the synonym: “phonography” or 2) by trimming the words to their root e.g. “sound record” and “phonograph”. There are two ways of evaluating our search - qualitatively or quantitatively. For this project we will conduct a qualitative analysis of the search's efficacy from the perspective of the client. This will take the form of a questionnaire sent out to UNDRFM members that simply asks if the results of the search were useful to its members.
When searching unstructured information using the retrieval methods discussed above the results are probabilistic – the web pages displayed 'probably' meet the needs of the user. The searches that users of the UNDRFM database perform are by contrast deterministic, that is, they definitely meet the needs of the user. They are very precise searches for information you know is there because it is your information and it is structured. IR uses natural language and Database searches use SQL:
The command: Select name from members; will produce a result that details all the members names.
Select organisation from websites where web id = 1; will display the website with the id 1 – London Sound Survey.
Select name, url
From members, websites
where published on = 1
and published on = web id;
Will display all the names of people who've work published on London Sound Survey's web site as well as the site's URL.
The grammar is very strict. Unlike natural language where if you err you may still be understood, the smallest mistake in the syntax of an SQL instruction means the computer will fail to read and execute the command. This is a problem with Databases in particular and web 1.0 technology in general – they require the developer to become a polyglot.
Bibliography
Macfarlane, A., Butterworth, R., Dykes, J., (2009) The Internet and the World Wide Web, London: City University
Macfarlane, A., Butterworth, R., Krause, A., (2009) Structuring and Querying Information Stored in Databases, London: City University
Macfarlane, A. (2009) Information Retrieval, London: City University
Musciano, C., & Kennedey, B., (2002) HTML & XHTML The Definitive Guide 5th Edition, Sebastopol CA: O'Reilly & Assoc.
Robertson, S.E., & Sparck Jones, K., (1997) Simple, Proven Approaches To Text Retrieval, London: City University.
Taylor, A G., (2010) SQL For Dummies 7th Edition, Hoboken NJ: Wiley Publishing INC.
SQL Course [online] Available http://www.sqlcourse.com/index.html
Search SQL Server [online] Available http://searchsqlserver.techtarget.com/
27/10/2011
Materialities of Text Online Conference
The book, in its traditional codex form, appears in transition from print media to digital media; a condition nevertheless complicated by its forms of survival, as indicated by the term ‘webpage’. Despite the epochal significance of the scroll, the codex, and the digital text, such material figures of inscription are necessarily hybrid; a hybridity that especially characterises the current historico-technical relation between print and digital media. Hybridity, of course, has been championed, for example, in postcolonial studies, as a figure of subversion, but it is also clear that hybrid text, as much as it is an object of possible democratisation within the digital public sphere, is also an object of intense capitalisation. Thus, the apparent waning of the hegemony of print is drawing questions of the politics of textual materialism into critical perception, and the need to interrogate the specificity of these materials, in their complex relations to the sensual form of paper and the ‘dispersed’ textuality of the digital medium.
What, then, are the new materialities of hybrid text-media? What are the politics of digital/print hybrids, artists’ books, writing technologies, and digital publishing? How does media hybridity transform the political book, the artists’ book, or the work of literature? What effects do new materialities of text have on patterns of reading? Has media process replaced the media object? What are the sensory forms of new media materialities? How is the commodity-form of the book altered by new media platforms? What are the conditions and forms of specific media hybridities? What does new media do to the ‘perversions’ of the book – to bibliomania, to fetishism? Are we still ‘people of the book’ – what remains of the authority of the book? How has independent publishing responded to new materialities of text? What might figures of the book offer in the way of new or counter-knowledges, forms of community and communication?
What, then, are the new materialities of hybrid text-media? What are the politics of digital/print hybrids, artists’ books, writing technologies, and digital publishing? How does media hybridity transform the political book, the artists’ book, or the work of literature? What effects do new materialities of text have on patterns of reading? Has media process replaced the media object? What are the sensory forms of new media materialities? How is the commodity-form of the book altered by new media platforms? What are the conditions and forms of specific media hybridities? What does new media do to the ‘perversions’ of the book – to bibliomania, to fetishism? Are we still ‘people of the book’ – what remains of the authority of the book? How has independent publishing responded to new materialities of text? What might figures of the book offer in the way of new or counter-knowledges, forms of community and communication?
13/10/2011
DITA Lecture 2
Some key terms that need to be undertood:
The Internet: is a vast network of networks connecting innumerable computers private, public, institutional, academic and governmental via electronic, wireless, and fibre-optic connections into one massive super-network. It is the infrastructure that makes the World Wide Web and electronic mail possible.
WWW: If the internet is the infrastructure then the WWW is a service that uses that infrastructure. It is a system of web pages connected by hypertext links. One either follows a link or types in a Universal Resource Locator (URL) address. The computer, via the web browser and web server, finds and gets the corresponding page from its networked host.
Hypertext is the text that appears on a web page. It contains links (hyperlinks) to other documents on the web that are accessible by clicking the hypertext. It is a key constituent of the web’s architecture.
HTML Hyper Text Mark Up Language. Describes the content of web pages it is not a programming language it is a mark up language that consists of mark up tags that usually come in pairs: a start tag and an end tag that are in <> brackets.
The Internet: is a vast network of networks connecting innumerable computers private, public, institutional, academic and governmental via electronic, wireless, and fibre-optic connections into one massive super-network. It is the infrastructure that makes the World Wide Web and electronic mail possible.
WWW: If the internet is the infrastructure then the WWW is a service that uses that infrastructure. It is a system of web pages connected by hypertext links. One either follows a link or types in a Universal Resource Locator (URL) address. The computer, via the web browser and web server, finds and gets the corresponding page from its networked host.
Hypertext is the text that appears on a web page. It contains links (hyperlinks) to other documents on the web that are accessible by clicking the hypertext. It is a key constituent of the web’s architecture.
HTML Hyper Text Mark Up Language. Describes the content of web pages it is not a programming language it is a mark up language that consists of mark up tags that usually come in pairs: a start tag and an end tag that are in <> brackets.
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