Dynamic Document Generation

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Dynamic Document Generator: Digital Scientific Papers as Decision Support Product

Dynamic generation is an approach based on the concept of Version Control. Documents are generated dynamically dependent on:

  • (Online Data Resouces) steadily updated online data resources (e.g. stock exchange, monitoring data about weather and climate data, ...),
  • (Geolocation) geolocation and dynamic content generation, that is depended on current time and geolocation of the teacher and learner.
  • (Time) documents can be generated time dependent (e.g. documents about Risk Management that include data of recent disasters from COPERICUS[1] about educational resource for risk mitigation according to the disaster that occured - bush fire, land slides, flooding, ...). Other examples of educational resources are for example insects, that deal with butterflies in summer and focus on survival strategy in winter, when the learner does not see them.

Generic requirements of dynamic content generation are:

  • (algorithm) the algorithms, how information is selected, filtered and displayed must be reproducible for other authors and learners to create in the dynamically generated document.
  • (data) the authors and learners must be able to view and check the source of the data, that is used for diagrams, prioritization in list of bullet points of recommendations. Users must be able to reproduce, prioritization with the underlying data.

Learning Task[edit | edit source]

Risk Management[edit | edit source]

  • (Risk Management) Disaster occur in space and time. They challenge the risk management organisations with unexpected requirements and constraints. Dynamic document generation can be used to support risk management team with short and very comprehensive documents that include
    • up-to-date maps for the assessing the damage of the disaster (e.g. [COPERNICUS Emergency Mapping Service,
    • available learning resources for risk mitigation that can be applied in the region, a specific teams currently operates in,
    • suggestions for tasks and recommendations that are relevant for region and the current time
  • (technical) explain how such dynamic content could be compiled tailored for the geolocation and current extent of the disaster. (i.e., tasks related to a location) assigned to and performed by human workers for a humanitarian purpose.
  • (Malaria Mapping) Take the humanitarian activities of HOT-OSM[2] for Malaria as a starting point to suggest dynamic content for field workers that contribute to missing maps[3]. The dynamic documents should support the field worker with information tailored to the geolocation of their work (see geolocated Open Educational Resources).

Learning Environment[edit | edit source]

(Tailored Documents for Learning Environments) Interesting places on earth (see Points of Interest - POI) can be augmented with dynamic content tailored for the expertise, age and social and cultural background of the learners. The specifications and constraints of the learner, teacher and learning environment determine the generation of documents for the specific requirements and contraints.

  • (COVID-19) During a pandemic or epidemiological outbreak data about cases, hospitalisation, death, ... are updated on a daily basis. Explain, why a dynamic document generation for reports or a updated statiscal analysis is important for automisation of report delivery!
  • (Requirements and Constraints Analytics) select features you want to incorporate in a Dynamic Document of learner and analyse the concept of tailored Wiki books.
  • (Digital Learning Environment) Explain the importance of Dynamic Document Management for the generation of tailored task for students. Link the dynamic document management to learner analytics. Explore KnitR for dynamic task management according to the learner profile of the student.
  • (Real-World Lab) Analyse a concept of a Real-World Lab and explain how that concept of benefits from tailored learning resources for the lab.
  • (3D Modelling) Explore the contribution of 3D modelling for linking digital representations to physical hands-on reprensentations in learning environment and combine digital 3D modelling and 3D printing of objects for the learning.[4]. Discuss the digital distribution learning objects (e.g. with OBJ-files) and its printing in remote schools and apply also the sustainable development goals to that concept.
  • (Learner Analytics Dashboard) Analyse the concept of OpenSource Shiny WebApps and check out a Dashboard structure for data visualisation (see Shiny Dashboard example). Design your learner analytics dashboard (first in LibreOffice) with options you would like to see and determine the of realtime interventions in the learning process you want to make! Discuss the result in your teacher education context. Addess also the issues of privacy of student data! Finally explore the Shiny Demo Gallery and identify feature that would help to design a Learner Analytics Dashboard. Explore the concept of AppLSAC for research projects and privacy aware usage in school or college with submission of learner data collected in a browser and stored only locally in the browser without submission to a remote server as AppLSAC.
  • (Tailored Learning Tasks) Assume that data is collected locally in learning environment with

Decision Support Systems[edit | edit source]

Assume scientist would produce not only a paper in a journal as publication of the scientific results, but also a digital product that can be used in decision support systems. If we combine e.g. the statistical and/or numerical results in a paper with the interpretation, then the interpretation and conclusion is easier to understand for reader of the scientific paper, while the underlying method and analysis can be used for supporting decisions.

  • Explore the concept of Fuzzy Logic and Fuzzy Controllers and explain how this approach can be helpful for integration of scientific results into decision support system!
  • How could collected data in the publication be used reproduce the decision support and the scientific result?
  • Analyse KnitR for document generation and identify, what is missing for a digital IT-product, that can be used for Decision Support Systems!

Economics[edit | edit source]

  • (Monitoring Data - Sensors) How would you use dynamic document generation for selling products? Collect a few examples!
  • (Business Analytics) A web search engine interprets the words in a search box as interest of the user in specific information. Analyse the results in the page, how they combine
    • educational content from other available information systems, that help to understand a certain topic and
    • advertisments according to the content in the search box (and if done by provider of web search engine) according to the user profile generated by previously collected data.
  • (Search and Key Words) Perform an analysis, how a dynamic document would look like for the search words flu fever over time. Create a document manually that would serve the needs of the information needs of the user and commercial desire of the provider to inject tailored advertisments in the dynamic document.
  • (Ethical Consideration) Analyse ethical aspects of dynamic content generation (e.g. if a user cannot assess, if the specific recommendation in the document is based on specific advertisments of a company or educational content that was quality assured by governmental agency or an academic institute).

News[edit | edit source]

  • News is relevant for majority of the population only a short period of time. In the news specific terminology is used, that needs further explanation depending on the target group of learner. Take a current example from newspapers and evening news on TV analyse for different target groups of learner the design of a dynamic paper dependent for the same topic/example you selected from the news. Target groups are:
    • Children in different ages (e.g. primary schools),
    • Adults with different professional background (e.g. field worker in developing countries, engineer, researcher, ...)
  • News about a finished project, e.g. a generated Transportation Map for Managua by Humanitarian Open Street Map Team[5]. Beside accessing the finalized map for Managua a dynamic document might include educational content how other communities could apply a similar collaborative mapping approach to their problem of a missing map as well and learn how to use the same tools as Humanitarian Open Street Map Team and further explaination why the map of a bus network[6] was so important for the cities in general and what are consequences for society, when these map do not exist (see Missing Maps[7]).

Technical Considerations[edit | edit source]

  • In dynamic documents one basic element are the definition of terminology, that is used in educational resources for students or for scientific publication, in which the terminology is defined, so that other scientist understand the semantics in which the terminology is used in the publication. Treat the "definition" as an content element, that is
    • either mentioned and cited in the dynamic document (static import),
    • or dynamically imported from a wikipedia section (dynamic import).
  • Describe the PROs and CONs of both approaches for dynamic document generation.
  • Explain the relevance of dynamic content generation for Spatial Decision Support Systems
  • Analyse KnitR and how it allows the manual document generation, build on dynamic data resource on the web.

See also[edit | edit source]

References[edit | edit source]

  1. COPERNICUS - Emergency Management Service, List of Activations - (accessed 2017/08/17) - http://emergency.copernicus.eu/mapping/list-of-activations-rapid
  2. HOT - Malaria Activities and Mapping Programme - URL: https://www.hotosm.org/impact-areas/public-health/ (sccessed 2020/04/22)
  3. Siemen, C., dos Santos Rocha, R., van den Berg, R. P., Hellingrath, B., & Albuquerque, J. P. D. (2017, March). Collaboration among humanitarian relief organizations and volunteer technical communities: identifying research opportunities and challenges through a systematic literature review. In Proceedings of the 14th ISCRAM Conference.
  4. Mintus Digital (2019) Application of 3D-Printing in Mathematics Education - URL: https://www.uni-siegen.de/nt/didaktik/mintus/mintus-digital/ (viewed 2020/04/22)
  5. The Humanitarian OpenStreetMap Team (HOT) applies the principles of open source and open data sharing for humanitarian response and economic development - https://www.hotosm.org/
  6. HOT - A crowd-sourced public transportation map for Managua 2016/01 - https://www.hotosm.org/updates/2016-01-07_a_crowd_sourced_public_transportation_map_for_managua - Generated Map: http://rutas.mapanica.net/mapa/
  7. Feinmann, J. (2014). How MSF is mapping the world’s medical emergency zones. BMJ, 349, g7540.