Presentation at Rhosygilwen, Pembrokeshire, 2nd April 2018.
Click on the link below to download the paper:
The Post Truth Forum website (www.posttruthforum.org) is a work-in-progress effort to collect and categorise online and in-print resources relating to Post-Truth issues.
A downloadable PDF extracted from the website provides a 33 page digest of some of these resources including quotes and excerpts grouped under broad headings including: Post-Truth Democracy & Free Speech; Propaganda & Misinformation (Foreign, Partisan & Computational); Fact Checking; Journalism; Information Literacy; Monetisation (Fake News, Political Advertising, Personal Tracking Data, Micro-targeting; Unintended Consequences; Personalised Search & The Filter Bubble; Social Media & Social Polarisation; Polarisation & Extremism. For a more in-depth topics and further updates vist the Post Truth Forum website.
This paper prepared by Gene Loh, a senior developer with Synaptica’s R&D team, reviews the open standards used to create Synaptica’s cultural heritage semantic image indexing application Linked Canvas.
Linked Data provides a natural platform for taxonomy management, and when used in concert with the International Image Interoperability Framework (IIIF) for accessing graphical image resources, provides an architecture that is suited to an image annotation application. The combination of Linked Data and IIIF specifications can be used to develop extensible discovery tools based on the Semantic Web Stack.
This is a brief post to say thank you to all the delegates at SSR@125 and #iskosg2017 who participated in the Post Truth Forum session. I am flying from Chennai to Washington DC to deliver another Post Truth Forum session at the Dublin Core 2017 conference.
All the great solution ideas provided in Chennai will be written up in this blog shortly after the Washington event.
Session 5 of the ISKO UK 2017 conference was titled False Narratives: developing a KO community response to post-truth issues. It comprised three presentations and a panel discussion. Following are summaries of all talks with links to slide decks and audio recordings provided by ISKO UK.
The summaries and audio recordings are created and curated by ISKO UK and available from the side-bar links at http://www.iskouk.org/content/sessions/session-5-false-narratives-developing-ko-community-response-post-truth-issues.
In 2016, two leading Western democracies, the UK and the US, held a referendum and an election that attracted criticism concerning the quality of information available to the voting public. The Internet and social media in particular were key battlegrounds during the 2016 elections. Internet search engines and social media technology companies have radically transformed how people search for information and how information producers feed content to their consumers. Among the unintended consequences of some of these technologies are an increase in political and social polarisation, as well as in the dissemination of false information. These phenomena have been so prominent that the Oxford Dictionary chose ‘post-truth’ as word of the year for 2016. Humanity cannot afford to accept post-truth as the new norm. Post-truth misinformation/disinformation threaten to undermine democratic processes, promote extremism, and destabilise society. These problems must be tackled, and both technological and social solutions are needed. How can the Knowledge Organization community address the challenge?
The expression ‘post-truth’ has been with us for a decade or more. The issue it describes – that there is no such thing as an objective ‘truth’ – has its roots in the centuries-old epistemological problem of knowledge as ‘justified true belief’.
The concept has gained fresh currency in light of the rise of populist political movements between 2015 and 2016. It presents us as information professionals with a central challenge – what should be our ethical response to the idea that there is no ‘truth’ and that data can be applied selectively to legitimise any political assertion?
In her recent address to the American Libraries Association, Hillary Clinton said, “As librarians, you have to be on the frontlines of one of the most important fights we’ve ever faced in the history of our country. The fight to defend truth and reason and evidence and facts.” In this session, CILIP CEO Nick Poole explored the consequences of undermining public trust in evidence, and the need for information professionals to re-state and defend the role of evidence, trust and literacy in information sources. You can read the full text on his blog dedicated to matters of post-truth.
Full Text Transcript: https://www.cilip.org.uk/news/evidence-trust-post-truth-world
‘Fake news’ is not a new concept; it dates back as far as storytelling itself – even Rameses the Great was guilty of it in 1200BC. But the speed and distribution by which false information can be spread has accelerated thanks to lowered cost of publication and distribution via the internet, and the difficulty of regulation. This presentation looks at the journalists’ perspective – and debates the ideas of journalists as purveyors of, and defenders against fake news. It questions whether the debate around fake news could actually prove beneficial for journalists, and how they can work to ensure that audiences become aware which information they can trust, including such innovations such as First Draft, Full Fact and Dminr.
Stella Dextre Clarke (Moderating) – Information Management Consultant, Chair ISKO UK and Vice-president, ISKO plus David Clarke – CEO Synaptica, Nick Poole – CEO CILIP and Dr. Glenda Cooper – Lecturer in journalism at City, University of London.
PostTruthForum.org was released today as a publicly accessible website. It provides a hierarchical menu of Discussion Topics relating to Post-Truth issues. Topics are grouped under headings for Causes, Effects and Solutions. Topics are then linked to Resources & Reference including books, websites, blogs and videos, as well as Webography of online citations and references.
To become a contributing editor of the site, or to provide comments and suggestions, please use the Feedback link on this blog.
On Tuesday September 12th the ISKO UK Annual Conference discussed fake news and post-truth issues, including a plenary discussion about Developing a Knowledge Organisation Community Response. This whiteboard captured the main takeaway ideas.
ISKO have recorded the speaker presentations and panel discussion for the Post-Truth session. The recording will be made available at ISKO UK’s website – announcement to follow once it is ready.
dc_admin | | About Truth | fake news, Glenda Cooper, information literacy, ISKO, monetising fake news, monetizing truth, Nick Poole, post-truth, Post-Truth KOS, Pro-Truth Alliance, WikiSearch | 0 Comments
ISKO is the International Society for Knowledge Organization. At the Annual Conference of ISKO UK on September 12th, 2017 I will be joining ISKO’s Vice Chair – Stella Dextre Clarke, CILP’s CEO – Nick Poole, and Dr. Glenda Cooper – Lecturer at City University, London, to discuss how the Knowledge Organization (KO) community can develop a response to post-truth issues.
Session 5: False narratives: developing a KO community response to post-truth issues
Location: Theatre Chair: Stella Dextre Clarke
Conference details at:
To download a PDF slide deck of the presentation click on the following link or image:
Knowledge Management is a powerful tool for improving the business results of any enterprise. It achieves this through engaging the enterprise in a concerted effort to optimise the use of knowledge assets, which include recorded information and methodologies as well as human experience and know-how.
KM is both a strategic and a tactical endeavour. It will fail without vision and leadership from the top. It will only succeed when all parts of the organisation collaborate to align people and resources toward a common goal.
KM is also a technical endeavour. It requires a systematic approach based on standards and best practices, as well as the support of software systems for managing knowledge organisation, discovery, and sharing.
The technologies and the methodologies used to organise, discover and share knowledge are the subject of this article. Academically this activity is firmly grounded in library and information science, but other disciplines are now playing an increasingly important role, including computer and data science, language engineering, linked data, social media and user experience design.
Organisation methods and practices started as soon as people began collecting knowledge in libraries. In the 3rd century BCE the poet and scholar Callimachus of Cyrene produced a 120 volume bibliographic catalogue of the half-million works held in the Library of Alexandria. The catalogue comprised indexes and tables of information including the title, author and subject, as well as brief biographies and abstracts.
In the late 19th century CE the American librarian and educator Melvil Dewey developed a hierarchically organized classification system. The Dewey Decimal Classification system was widely adopted by libraries around the world and is still in use today. In the 20th Century CE the Indian mathematician and librarian S. R. Ranganathan devised a facetted classification system (colon classification), supporting much greater indexing specificity.
Library classification schemes were primarily designed to place physical books on to physical shelves. This posed an immediate knowledge organisation challenge. A physical book can’t be in two places at the same time, but many books span multiple subjects and justify being accessible under more than one heading.
The problem was overcome by creating indexes. These can provide access to a book under the multiple subject headings that it is about, as well as by title, author, and other parameters.
Simple card indexes grew in size and complexity, taking the form of alphabetical and hierarchical indexes of subjects, places and people. Libraries standardized the terminology they used by creating ‘controlled vocabularies’ and ‘authority files’, such as the Library of Congress Subject Headings.
When information was stored digitally rather than on paper, computers could search the full text of books and documents at lightning speed. For a while some people thought that they no longer needed the knowledge organisation tools and methods developed by libraries.
Most enterprises came to realize, however, that full text search has its own limitations. Search can find specific words or phrases but it has no understanding which words and phrases are significant; it doesn’t understand what a document is about. Additionally, because one word can refer to different things and one thing can be described by different words, full text searching is necessarily imprecise. For every relevant document returned a user may have to wade through hundreds or thousands of irrelevant documents.
A more insidious problem is that some relevant documents will never be seen because the language used by the searcher doesn’t match the language used by the author.
KOS are formally structured schemes that describe collections of like-things such as subjects, people and places. They disambiguate words that can have multiple meanings, and also map together variant terms for the same concept. Relationships assert facts about how concepts and entities relate to one another.
Numerous national and international standards are available to help guide the design of KOS schemes, foremost among them are ISO 25964 and W3C SKOS and OWL.
One of the most exciting innovations in the management of knowledge is the prolific growth of Linked Data. Linked Data allows diverse datasets to be recombined in novel ways. This can be kept behind the firewall as Linked Enterprise Data or exposed to the world as Linked Open Data. Linked Open Data provides a framework for the entire planet to share knowledge. When different user communities and perspectives come together and collaborate, our collective knowledge is enriched in the process. Any organisation can start tapping into a wealth of structured knowledge currently available as Linked Open Data. Organisations that fail to embrace the Linked Data opportunity may struggle to keep up with those who do.
Words and phrases found in content may be individually annotated by linking them to the most specific concepts and names they discuss or represent. Larger sections of content including complete documents can be classified to the broader categories they are about. The indexing process can also extract concepts and names from content and submit them as candidates for inclusion in the ontology. Natural Language Processing (NLP) techniques analyze the text and metadata of content. The indexing process leverages the semantic relationships of the ontology to determine the context of words and phrases within the text and then match them to disambiguated concepts in the ontology.
Concepts and names within an enterprise ontology may be mapped to equivalents in external ontologies. Alternatively, external ontologies may be adopted and used directly as reference authorities. When internal content is indexed or mapped to external resources then additional information contained in those resources can be retrieved. For example, text analysis may identify that a document mentions ‘London’ and that this refers to London, England as distinct from London, Ontario. Once the named entity has been unambiguously identified it can be mapped to equivalent entities in resources like DBpedia and GeoNames. These resources can then deliver additional information such as latitude and longitude coordinates, population statistics, maps, images and data on industry, commerce and government.
Indexing content can be a fully manual process, a fully automated process, or most often a mixture of the two. Automation involves the use of Named Entity Recognition (NER) and Natural Language Processing (NLP) systems. It also uses the semantic relationships found within Knowledge Organisation Systems plus general-purpose lexicons and grammatical parsers, along with custom built indexing rules and machine learning processes. Modular NLP components can be assembled to create a finely-tuned semantic indexing pipeline.
During the prototyping phase tools may be employed to create reference training sets using consensus-based human indexing. NLP and NER processes may then be tested against the training sets and optimized. After the prototyping phase, corpora, ontologies and NLP/NER processing resources may be compiled into a semantic annotation application.
We first discover knowledge about the world directly through our senses. Through touch, smell, taste, sight and sound. We then discover knowledge vicariously through books, media and dialogue with other people.
In the digital age most of the vicarious information we receive is delivered via computers and mobile devices. Screens have become the medium between people and knowledge. Knowledge discovery is the end-game of knowledge organisation.
There are three fundamentally different ways that humans interact with information systems: (i) Search, which starts with a user’s expression of their question (usually one or two keywords) and then follows iterative refinement; (ii) Browse, which starts with the system presenting organized lists or graphs of related things and then follows the user’s chosen pathway; and (iii) Discovery, which happens when the user’s search or browse experience is interrupted upon the surfacing of relevant concepts or content that were not present in the user’s initial query.
The presentation slides accompanying this talk provide five examples illustrating how Knowledge Organisation Systems support knowledge discovery.
In example 1 below the user searched on “love” – the Knowledge Organisation System was accessed to identify artworks and specific figurative details that are about the concept of love regardless of what words may actually exist in the content.
In example 2 below the user pans and zooms around images and the Knowledge Organisation System responds by dynamically updating a discovery panel to reveal the concepts related to what is in view.
In example 3 below the user browses alphabetical and hierarchical lists of concepts and visual features and the system responds by opening the image and panning and zooming to the specific visual details.
In example 4 below the Knowledge Organisation System works behind the scenes to facilitate the discovery of conceptually related content. Using Linked Open Data KOS opens more gateways to discover related external content from sources such as DBpedia.
Finally, example 5 illustrates how Knowledge Organisation Systems and Linked Open Data ontologies allow enterprises to ‘search outside the box’ of their own content, enabling questions to be answered where the relevant data does not exist within the enterprise’s internal content. The example uses NLP technology to identify people within news articles. The people are then semantically indexed using named entities in external biographical ontologies. The external biographical data can then be queried along with the internal news content.
This technique enables powerful queries to be performed, such as find news articles about politicians born in England who are under the age of 50 and hold cabinet positions. The internal content only has to mention the names of people within the text. The rest of the query can be answered by referencing knowledge contained in external KOS ontologies.
KM and KO can help enterprises to create, preserve and disseminate actionable knowledge. At the level of knowledge organisation and discovery the key challenge is to help people to see both the forest and the trees. To optimise search and find the needle in the haystack, while also being able to contextualise how resources relate to one another. It addresses the challenges of retrieval, and relevance.
As digital data continues to grow exponentially the need for knowledge organisation tools only increases. We need systems that can index documents by all the significant concepts they discuss and then summarize what each document is about. Controlled vocabularies and authority files are key enablers in this endeavour.
This article is based on a presentation to the Global Management Congress in Mumbai, June 2016, delivered by Gene Loh on behalf of David Clarke upon acceptance of the Knowledge Management Leadership Award.
Visual images are a powerful medium for communicating ideas and information, and they provide a valuable complement to textual content. A vast amount of information resides inside photographs, paintings, diagrams and drawings which is comprehensible to the human eye but until recently has been relatively inaccessible to machine queries.
‘Access to image-based resources is fundamental to research, scholarship and the transmission of cultural knowledge. Digital images are a container for much of the information content in the Web-based delivery of images, books, newspapers, manuscripts, maps, scrolls, single sheet collections, and archival materials.’
Well established techniques exist to support searching and browsing images based on metadata applied to the whole image, but search and browse access to specific points or regions within images is a relatively immature field.
Image-level metadata may be sufficient for information access to the majority of images, but image-level metadata is insufficient to support access to large or complex images. Examples from art, science and current affairs are considered.
Figure 1 below portrays The Garden of Earthly Delights by Hieronymus Bosch, which is an allegorical work of art with dense figurative detail. The painting’s narrative is built up from many separate scenes, each telling a story that is rich in allusion and symbolism. Metadata applied to the whole image does not enable the viewer to locate or interpret the various different scenes and figures in the work.
Figure 1: The Garden of Earthly Delights, Hieronymus Bosch, c. 1503
Figure 2 below presents an image of the Earth’s moon. Metadata applied to the whole image does not enable the viewer to identify topographic features or the location of the Apollo landing sites.
Figure 2: Full Moon, Gregory H. Revera, 2010
Figure 3 below presents a photograph of ten international leaders at the G8 Summit in Lough Erne Northern Ireland on 18th June 2013. Image level metadata can describe the names and titles of the people in the photograph, but not match the specific names to each individual.
Figure 3 Leaders of the G8, 2013
In all three of the examples, while a certain level of information access can be supported by image-level metadata, a much richer knowledge discovery experience can be provided if specific visual details are individually identified.
An analogy with information access to physical books illustrates the value proposition for sub-image annotation.
In a physical library, card catalogues and bibliographic databases provide a means to identify shelves of books and individual books. Tables of contents and subject indexes then facilitate a deeper level of information access to specific pages, sections and paragraphs within a book.
Image-level metadata may be compared with card catalogues and bibliographic databases. They take the user to a discrete work but cannot take the user inside the work to discover its interior content. Sub-image annotation may be compared with tables of contents and subject indexes. They allow the user to search and to navigate inside images.
Image-level metadata describes the whole image. At a minimum, descriptive properties usually include an image title, long description, date and creator. They could also record metadata automatically captured by cameras according to the Exif standard. Different knowledge domains and disciplines will also each have the need to capture additional information. In the cultural heritage community it may be desirable to distinguish the date and creator of the photograph from the date and creator of the object depicted in the photograph, and to add provenance information about the depicted object. The image-level metadata may be further extended and linked to collection management system records. In the healthcare and life-sciences community it may be desirable to include metadata captured according to the AIM or DICOM standards.
A generalized prescriptive approach to image-level metadata would fail to satisfy most real-life user needs, which require image-level metadata to be an extensible ontology. A base set of properties and attributes need to be defined for any knowledge domain and then be quickly and easily extended. Image-level metadata provides a catalogue of the images in a collection. The metadata elements need to support faceted search and navigation of the collection.
Sub-image-level metadata, also referred to as annotation metadata, describes particular points of interest or regions of interest in an image. At a minimum, descriptive properties usually include an annotation label and longer description. Additional metadata is required to define the spatial co-ordinates of the point or area and the level of zoom defined for the point or region. Spatial co-ordinates may be expressed in pixels offset from the top-left corner or in percentages of the width and height.
As with Image-level metadata extensibility is essential in order to meet the real-world needs of users in a diversity of knowledge domains and disciplines. Annotation metadata provides an inventory of the visual features within an image. This metadata can support search inside functions and table-of-contents style browsable navigation.
Further posts in this section will explore specific use cases and emerging standards, as well as a discussion on the benefits of semantic indexing and Linked Data.
Post-truth is a cultural phenomenon where objective facts are less influential in shaping public opinion than appeals to emotion and personal belief. In a post-truth culture people assert and defend their opinions without regard to facts or logic. In a post-truth culture consumers of information may also choose to suspend judgement about the authenticity or credibility of information, provided that it supports their existing beliefs. Post-truth culture is different from a culture in which alternative opinions about what is true are contested; it is a culture that has ceased to value truth itself.
Please watch my explainer video to get a quick overview of some of the issues surrounding post-truth.
Post-truth issues have both societal and technological causes and effects. Evidence suggests that developments in the way Internet technology is used, particularly social media and search personalisation, are responsible for an explosion of post-truth phenomena. The effects of post-truth phenomena on society are profoundly harmful; they include political polarisation, extremism, social divisiveness, electoral interference and the destabilisation of democratic processes.
Causes, effects, trends and solutions will be discussed in subsequent posts.