ClioWire: Difference between revisions
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We suggest to try to model our historical knowledge as an immense collection of Pulses. | We suggest to try to model our historical knowledge as an immense collection of Pulses. | ||
ClioWire is constructed around the reintrepreation of two existing concepts : the concept of hashtag, the concept of bots, the concept of | ClioWire is constructed around the reintrepreation of two existing concepts : the concept of hashtag, the concept of bots, the concept of front ends. The hashtage is much more than a convienent way for tagging content, it is a fundamental mechanism for coordinating semantics in extremely large distributed systems. Bot are much more than just funny users posting strange things on Twitter or helpers for Wikipedia, they are a new way of conceiving software engineering for large-scale projects. Front-ends are not just front end on mastered back-end, they can also be operates as interactive tools on data they are not mastering. The combination of these three concepts create a novel technological ecosystem for knowledge management and production. | ||
Cliowire is constructed around the ideas of smooth semantization in contrast with right and formal models which in practive have difficulties to be adopted in large distributed systems. | Cliowire is constructed around the ideas of smooth semantization in contrast with right and formal models which in practive have difficulties to be adopted in large distributed systems. | ||
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Simple models of distributed coordination https://infoscience.epfl.ch/record/187558/files/cs-kaplan05.pdf | Simple models of distributed coordination https://infoscience.epfl.ch/record/187558/files/cs-kaplan05.pdf | ||
=== Folksonomy and emergent classification systems === | |||
== Rigid semantization vs smooth semantization == | == Rigid semantization vs smooth semantization == | ||
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Contrastring the pro and cons of two approaches to the semantization process. | Contrastring the pro and cons of two approaches to the semantization process. | ||
== The | == The hashtag is a pivotal symbol == | ||
===Origins === | ===Origins and chronology === | ||
The US pound sign, number sign or hash symbol "#" is often used in information technology to highlight a special meaning | The US pound sign, number sign or hash symbol "#" is often used in information technology to highlight a special meaning | ||
| Line 85: | Line 87: | ||
1988: The pound sign was adopted for use within IRC networks circa 1988 to label groups and topics | 1988: The pound sign was adopted for use within IRC networks circa 1988 to label groups and topics | ||
===Pragmatics of the hashtag in social media === | 2007: Introduction of The Hastag use on Twitter, inspired by the IRC practice of channels | ||
2009: Hyperlink of all hashtags in tweets to Twitter | |||
2010: Instagram is launched in 2010 and starts using hashtags | |||
2010: Introduction of "Trending Topics" on the Twitter front page | |||
2010: Arab Spring and the European anti-austerity movement, which both used hashtags to brand what they were doing. | |||
2011: Occupy Wall Street hashtag. Hashtag for just-in-time information about protest activity. | |||
=== Pragmatics of the hashtag in social media === | |||
Hashtags have developed beyond their search function to convey context information. From #NIPS2017 to #soproud | |||
Recreating context despite asychrnony. | |||
No one owns or administers a tag channel. A channel is created the first time someone posts a status with a channel tag. http://factoryjoe.com/blog/2007/08/25/groups-for-twitter-or-a-proposal-for-twitter-tag-channels/ | |||
Enough people started using them eventually that in 2009 Twitter decided to embrace them. | Enough people started using them eventually that in 2009 Twitter decided to embrace them. | ||
| Line 95: | Line 116: | ||
"Twitter facilities one-to-many, asynchronous communication, and so tweeters are unlikely to be able to assume that they share contextual assumptions with all or any of their audience. By allowing tweeters to make their intended contextual assumptions accessible to a wide range of readers, hashtags facilitate the use of an informal, casual style, even in the unpredictable and largely anonymous discourse context of Twitter." | "Twitter facilities one-to-many, asynchronous communication, and so tweeters are unlikely to be able to assume that they share contextual assumptions with all or any of their audience. By allowing tweeters to make their intended contextual assumptions accessible to a wide range of readers, hashtags facilitate the use of an informal, casual style, even in the unpredictable and largely anonymous discourse context of Twitter." | ||
The pragmatics of hashtags: Inference and conversational style on Twitter / http://www.sciencedirect.com/science/article/pii/S037821661500096X | "The length restriction and the need to abbreviate and omit elements of the messages mean that the tweeter has to depend on her readers to be able to reconstruct the full intended message from the non-standard, abbreviated forms." | ||
Tweeters are, therefore, writing for an “imagined audience” (Marwick and boyd, 2010; Brake, 2012; Litt, 2012). | |||
as boyd (2010:46) notes, the discourse context does not persist, and “what sticks around may lose its essence when consumed outside of the context in which it was created”. | |||
"The hashtag, I suggest, has been appropriated to act as a highlighting device. It allows the tweeter to make certain contextual assumptions highly accessible, and thus guides the hearer to the intended overall interpretation in the most efficient and economical manner." | |||
From The pragmatics of hashtags: Inference and conversational style on Twitter / http://www.sciencedirect.com/science/article/pii/S037821661500096X | |||
The hashtag was not created for Twitter. The hashtag was created for the internet. | The hashtag was not created for Twitter. The hashtag was created for the internet. | ||
Because of its widespread use, hashtag was added to the Oxford English Dictionary in June 2014 https://www.theregister.co.uk/2014/06/13/hashtag_added_to_the_oed/ | |||
Ref: | |||
An Oral History of the Hashtag: https://www.wired.com/2017/05/oral-history-hashtag/ | An Oral History of the Hashtag: https://www.wired.com/2017/05/oral-history-hashtag/ | ||
The pragmatics of hashtags: Inference and conversational style on Twitter / http://www.sciencedirect.com/science/article/pii/S037821661500096X | |||
Kathleen Ferrara, Hans Brunner, Greg Whittemore Interactive written discourse as an emergent register / http://journals.sagepub.com/doi/10.1177/0741088391008001002 | |||
danah boyd Social network sites as networked public: affordances, dynamics and implications Z. Papacharissi (Ed.), Networked Self: Identity, Community and Culture on Social Network Sites, Routledge, Abingdon (2010), pp. 39-58 | |||
https://www.danah.org/papers/2010/SNSasNetworkedPublics.pdf | |||
Chris Messina Groups for Twitter; or a proposal for Twitter tag channels (2007) Available from: http://factoryjoe.com/blog/2007/08/25/groups-for-twitter-or-a-proposal-for-twitter-tag-channels/ | |||
MacArthur, Amanda, n.d. The History of Hashtags: Shedding Some Light on the History of Hashtags and How We’ve Come to Use Them. Available from: http://twitter.about.com/od/Twitter-Hashtags/a/The-History-Of-Hashtags.htm | |||
=== Hashtag, from lingua franca to universal language === | === Hashtag, from lingua franca to universal language === | ||
* A way to highlight to increase the signal / noise ratio | |||
* A way to desambiguiate giving universal ID | |||
* A way to compress complex context using ready-made chunks | |||
Hashtag is a way of indicating that a word is part of universal language | Hashtag is a way of indicating that a word is part of universal language | ||
Hashtags as highlighting devices: In its original functionality, this enabled a reader to find related content amidst the noise (Page, 2014) | |||
ready-made chunks or schemas describing often-encountered sequences of actions or events”. A form of linguistic compression of context. | |||
No body own hashtags. Goods and bad. | |||
The transition from normal language to universal language | |||
In one-to-many “broadcast communication”, such as Twitter, the message is adressed to “whoever finds it relevant” (Sperber and Wilson, 1986/95:158). As Sperber and Wilson (1986/95:158) | |||
ref : | |||
https://www.hashtags.org/ | |||
=== Hashtag and machine-readable ontologies === | === Hashtag and machine-readable ontologies === | ||
== Retweeting as versioning == | |||
Versioning in Wikipedia | |||
== Attribution ID for entities and predicates == | == Attribution ID for entities and predicates == | ||
| Line 129: | Line 192: | ||
== Machine2Machine == | == Machine2Machine == | ||
Relevance constraint (Sperber and Wilson) in Machine2Machine communication. Could we see a similar optmization effect | |||
== Interstitial Medium == | == Interstitial Medium == | ||
Latest revision as of 10:59, 15 December 2017
Presentation
ClioWire is the platform developed by the EPFL Digital Humanities master students and the members of the EPFL Digital Humanities Lab (DHLAB). The platform is an hybridation between Twitter and Wikipedia. The ambition of this platform is to curate simple open bricks for historical knowledge, shaped as short texts. It is meant to be based on no prefixed ontology, but collectively negotiated conventions, reformatting by bots and visualization by dedicated apps. This is what works well on Wikipedia and in our Digital Humanities bachelor course. It is meant to offer easy onboarding, i.e. the process in which one get accustom to a new system/platform (even for beginners and people with only very basic IT skills). This is what works well on Twitter. One goal is to offer simple and robust long-term archiving for bricks of historical knowledge.
ClioWire curates Pulses as basic bricks for historical knowledge. They constitute some sort of minimal information unit coding relationship between entities and sources. They typically encode what is usually referred as events. Pulses are artificial construction that can be continuously being remolded and combined in order to create greater pieces of knowledge. We suggest to try to model our historical knowledge as an immense collection of Pulses.
ClioWire is constructed around the reintrepreation of two existing concepts : the concept of hashtag, the concept of bots, the concept of front ends. The hashtage is much more than a convienent way for tagging content, it is a fundamental mechanism for coordinating semantics in extremely large distributed systems. Bot are much more than just funny users posting strange things on Twitter or helpers for Wikipedia, they are a new way of conceiving software engineering for large-scale projects. Front-ends are not just front end on mastered back-end, they can also be operates as interactive tools on data they are not mastering. The combination of these three concepts create a novel technological ecosystem for knowledge management and production.
Cliowire is constructed around the ideas of smooth semantization in contrast with right and formal models which in practive have difficulties to be adopted in large distributed systems.
Main characteristics
Their main characteristics are the following
- Pulses are 140-character long textual sequence (like tweets) (this constraint may be dropped)
- Syntax of Pulses follows some (evolving) conventions but no strict rules (like tweets)
- Pulses can be written by humans or by machine, and read by humans or machines (like tweets).
- Pulses have a first author but can be modified and rewritten by anyone. They are fundamentally considered as a common good (unlike tweets)
- Sequences of pulses are fully versioned. The history of their modification can be visualized (unlike tweets)
- Pulses can be attached to geographical coordinates, temporal coordinates, sources (URLs), document segments
- Each Pulses as a unique universal ID (like tweet), that can serve as reference in other Pulses and on the web.
- Pulses can be tagged as dubious or any other classification characterizing the trust one can have. The tagging itself can be partly done by bot (like for tweets)
- In sum, tweets are particular kind of Pulses, but Pulses are more general than tweets
The managing system for Pulses enables to do the following operations
- Inserting massive numbers of Pulses based on existing sources. If a bot imports Pulses massively, it will be their first author.
- More generally applying bot operation at a massive scale on Pulses (like for Wikipedia)
- Retrieving all the Pulses mentioning an entity (people, place) and visualizing them as timelines or maps or both.
- Retrieving all the intervention of a given user (i.e creation or editing of Pulses)
- Retrieving all the Pulses mentioning a given source (URL)
- Visualizing the editing history a sequence of Pulses
- Mapping the worldwide activity of Pulses
- Computing the list of the most active user, the most edited Pulses (like in Wikipedia)
- More things in the same spirit …
Self-organization of semantic conventions
State of the art in self-organizing conventions and emergent semantics
This section is under construction. Below some (quite old) references
Emergent Semantics for the Semantic Web
https://link.springer.com/chapter/10.1007/978-3-540-24571-1_2
Aberer :
Ouksel, M., Ahmed, I.: Ontologies are not the panacea in data integration: A flexible coordinator for context construction. Journal of Distributed and Parallel Databases 7(1) (1999)
Ouksel, M.: A Framework for a Scalable Agent Architecture of Cooperating Heterogeneous Knowledge Sources. Springer, Heidelberg (1999)
McCool, R., Guha, R.V.: Tap, building the semantic web
Flake, G.W., Lawrence, S., Giles, C.L., Coetzee, F.M.: Self-organization and identification of web communities. IEEE Computer 35(3), 66–70 (2002)
Hauswirth, M., Datta, A., Aberer, K.: Efficient, self-contained handling of identity in peer-to-peer systems
Ren, Wei; Beard, R. W.; Atkins, E. M. (8–10 June 2005). "A survey of consensus problems in multi-agent coordination". 2005 American Control Conference: 1859–1864. doi:10.1109/ACC.2005.1470239.
Mathematical and Multi-agent models for Self-organizing vocabularires
Simple models of distributed coordination https://infoscience.epfl.ch/record/187558/files/cs-kaplan05.pdf
Folksonomy and emergent classification systems
Rigid semantization vs smooth semantization
Contrastring the pro and cons of two approaches to the semantization process.
The hashtag is a pivotal symbol
Origins and chronology
The US pound sign, number sign or hash symbol "#" is often used in information technology to highlight a special meaning The hashtag may contain letters, digits, and underscores.
1970: The number sign was used to denote immediate address mode in the assembly language of the PDP-11.
1978 : Brian Kernighan and Dennis Ritchie used # in the C programming language for special keywords that had to be processed first by the C preprocessor
https://en.wikipedia.org/wiki/The_C_Programming_Language
1986 SGML standard, ISO 8879:1986 (q.v.), # is a reserved name indicator (rni) which precedes keyword syntactic literals, --e.g., the primitive content token #PCDATA, used for parsed character data.
1988: The pound sign was adopted for use within IRC networks circa 1988 to label groups and topics
2007: Introduction of The Hastag use on Twitter, inspired by the IRC practice of channels
2009: Hyperlink of all hashtags in tweets to Twitter
2010: Instagram is launched in 2010 and starts using hashtags
2010: Introduction of "Trending Topics" on the Twitter front page
2010: Arab Spring and the European anti-austerity movement, which both used hashtags to brand what they were doing.
2011: Occupy Wall Street hashtag. Hashtag for just-in-time information about protest activity.
Pragmatics of the hashtag in social media
Hashtags have developed beyond their search function to convey context information. From #NIPS2017 to #soproud Recreating context despite asychrnony.
No one owns or administers a tag channel. A channel is created the first time someone posts a status with a channel tag. http://factoryjoe.com/blog/2007/08/25/groups-for-twitter-or-a-proposal-for-twitter-tag-channels/
Enough people started using them eventually that in 2009 Twitter decided to embrace them.
The hashtag "was created organically by Twitter users as a way to categorize messages."
"Twitter facilities one-to-many, asynchronous communication, and so tweeters are unlikely to be able to assume that they share contextual assumptions with all or any of their audience. By allowing tweeters to make their intended contextual assumptions accessible to a wide range of readers, hashtags facilitate the use of an informal, casual style, even in the unpredictable and largely anonymous discourse context of Twitter."
"The length restriction and the need to abbreviate and omit elements of the messages mean that the tweeter has to depend on her readers to be able to reconstruct the full intended message from the non-standard, abbreviated forms."
Tweeters are, therefore, writing for an “imagined audience” (Marwick and boyd, 2010; Brake, 2012; Litt, 2012).
as boyd (2010:46) notes, the discourse context does not persist, and “what sticks around may lose its essence when consumed outside of the context in which it was created”.
"The hashtag, I suggest, has been appropriated to act as a highlighting device. It allows the tweeter to make certain contextual assumptions highly accessible, and thus guides the hearer to the intended overall interpretation in the most efficient and economical manner."
From The pragmatics of hashtags: Inference and conversational style on Twitter / http://www.sciencedirect.com/science/article/pii/S037821661500096X
The hashtag was not created for Twitter. The hashtag was created for the internet.
Because of its widespread use, hashtag was added to the Oxford English Dictionary in June 2014 https://www.theregister.co.uk/2014/06/13/hashtag_added_to_the_oed/
Ref:
An Oral History of the Hashtag: https://www.wired.com/2017/05/oral-history-hashtag/
The pragmatics of hashtags: Inference and conversational style on Twitter / http://www.sciencedirect.com/science/article/pii/S037821661500096X
Kathleen Ferrara, Hans Brunner, Greg Whittemore Interactive written discourse as an emergent register / http://journals.sagepub.com/doi/10.1177/0741088391008001002
danah boyd Social network sites as networked public: affordances, dynamics and implications Z. Papacharissi (Ed.), Networked Self: Identity, Community and Culture on Social Network Sites, Routledge, Abingdon (2010), pp. 39-58 https://www.danah.org/papers/2010/SNSasNetworkedPublics.pdf
Chris Messina Groups for Twitter; or a proposal for Twitter tag channels (2007) Available from: http://factoryjoe.com/blog/2007/08/25/groups-for-twitter-or-a-proposal-for-twitter-tag-channels/
MacArthur, Amanda, n.d. The History of Hashtags: Shedding Some Light on the History of Hashtags and How We’ve Come to Use Them. Available from: http://twitter.about.com/od/Twitter-Hashtags/a/The-History-Of-Hashtags.htm
Hashtag, from lingua franca to universal language
- A way to highlight to increase the signal / noise ratio
- A way to desambiguiate giving universal ID
- A way to compress complex context using ready-made chunks
Hashtag is a way of indicating that a word is part of universal language
Hashtags as highlighting devices: In its original functionality, this enabled a reader to find related content amidst the noise (Page, 2014)
ready-made chunks or schemas describing often-encountered sequences of actions or events”. A form of linguistic compression of context.
No body own hashtags. Goods and bad.
The transition from normal language to universal language
In one-to-many “broadcast communication”, such as Twitter, the message is adressed to “whoever finds it relevant” (Sperber and Wilson, 1986/95:158). As Sperber and Wilson (1986/95:158)
ref :
Hashtag and machine-readable ontologies
Retweeting as versioning
Versioning in Wikipedia
Attribution ID for entities and predicates
Negociation syntax
Bot oriented architecture
History of the concept of bot
Bots on Twitter
Bots on Wikipedia
Machine2Machine
Relevance constraint (Sperber and Wilson) in Machine2Machine communication. Could we see a similar optmization effect
Interstitial Medium
App/Shelves/Front-end
Back-end independent front-ends
Search engines
Visualization
Catalogs
Network
Examples of bots
Examples of negotiated conventions and bot usage
Below is the results of a small scaled negotiation between the first 8 cliowire developers.
Coding Pulses
Someone may simply write in natural language, without any source or conventional naming
- Francesco Raspi lived on the Rialto Bridge.
However, this Pulse may being tagged as unreliable. It is better to automatically produce a Pulse.
- Francesco Raspi is the owner of parcels 514 in the Napoleonic Cadaster of 1808.
In order to increase possible articulatation between Pulses, hashtags can be used. Like for Twitter, there are no predefined hashtags but communities can negociate common ways to articulate the content of pulses. A community may decide to use very generic hashtag in order to increase the potential for generic processing. The list below reflects the current practice and on-going negociation in the community.
Entities
Each entities (Place, people, book, segment, volume, etc) is associated with a unique hastag.
Example: #MarinoZorzi is an entiy
Predicate #Eq
Predicate #Eq defines the commutative equivalence between two entities. This means that one can be replaced by another. It can be used to disambiguate mentions.
Syntax: (Entity or URL) #Eq (Entity or URL)
- Ex: #MarinoZorzi #Eq #MarinoZorzi34
- Ex: #MarinoZorzi #Eq http://..
Predicate #In
Predicate #In defines that one entity is a subpart / is included in another
Syntax: #In Entity Entity
- Ex: #Venice #In #Italy
- Ex: #PietyandPatronage_p3 #In #PietyandPatronage
- Ex: #YoungFilmmakers #In #Filmmaker
- Ex: #T_FrenchRevolution #In #T_XVIIIcentury
The syntax entity #In entity is for the moment prefered to the syntax #In entity entity, but this is subject to negotiation.
Predicate #Mention
The Hashtag #Mention is used to indicate the presence of an entity in a document. In transcription processes the resulting transcription is created as an entity . This entity will be disambiguate later on by the #Eq hashtag.
Syntax: #Mention #Entity #In #Volume #Source URL (opt #Prob_score)
- Ex: #Mention #Francesco_554eacdd_6734_4c91_9b9a_5e40869403e7_000490_942_5513_363_139 #In #554eacdd_6734_4c91_9b9a_5e40869403e7 #Source https://images.center/iiif/554eacdd-6734-4c91-9b9a-5e40869403e7-000490/942,5513,363,139/full/0/default.jpg
* Ex: #Mention entity entiy entiy #In Volume
Predicate #Tag
Syntax:
- Ex: #Tag #JeanLouisNicollier #realisateur #T_1998 URL
Predicate #Copresence
Syntax: #Copresence #entity #entity #In #volume/#entity
- Ex: #Copresence #FrancescoRaspi #BaptistaNanni #In #PietyandPatronage_p3
Copresence could be replace by the general syntax of #Mention with several entities.
Predicate #Creator
Syntax: #Creator #entity #entity
- Ex: #Creator #PietyandPatronage #WannaGoffen
Temporal Entity #T_
- Ex: #T_1998
- Ex: #T_1998_2000
- Ex: #T_FirstCentury
- Ex: #T_FrenchRevolution
Condition #When
- Ex: #AdamSmith #In #Economists #When #T_1753
Condition #Where
- Ex: #AdamSmith #In #Economists #Where #London
Condition #Source
- Ex: #AdamSmith #In #Economists #Source #p14_LeTemps
Coding knowledge
Pulses can also be used to code knowledge ungrounded in Space and Time like:
- Francesco Raspi is the son of Domenico Raspi
Or better:
- SonOf #FrancescoRaspi #DomenicoRaspi in http://…
Attributing ID
Pulses can be used to document segment, artwork images and other entities that do not typically receive conventional name can receive a unique Id (possibly generated automatically). This tends to be done using the #eq predicate.
- #ImprintingCini434 #eq http://…
Coding inferred facts
Pulses can be used to code inferred fact like
- Francesco Raspi is the grandson of Giovanni Raspi (inferred base on Pulse1, Pulse2 and Pulse3 and Rule3)
Encoding Rules
Inferring rules may also be coded with Pulses (using convention of variables)
- R: If ($A is the son of $B) and ($B is the son of $C$) then ($A is the grandson of $C)