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The goal of this checkpoint is to find the research question to be answered, build a custom conceptual model to answer the question and find relevant data sources that could help answer the question.
The first two tutorials show the introduction to sample problems and introduce the way of thinking about data description as concepts, that may be filled from various sources. Tasks in the first checkpoint focus mainly only on those concepts.
Based on the offered topics and sample questions formulate your own question, or formulate your own question on your own topic.
Questions are sorted out by the topics.
Topic Protected sites offers following questions:
The topic Animal species is based on the natural taxonomy of the animal kingdom. We offer the following questions:
Deliver a PDF file consisting of 1-2 pages describing
On the next tutorial, everyone will tell the others the question and topic and list of available datasets (2 mins max).
Choose a research question from the list provided or come up with your own question. Consult the question with the lecturer – all proposed questions have some solution and require integration of datasets from various sources in order to answer it. Questions created by students shall be equally complicated to answer and the solution shall exist. Specify the questions for specific space and time.
The conceptual model represents a visualization of the knowledge needed to answer the question. An essential part of the task is to unambiguously define all the terms used in the conceptual model. Based on the nature of the problem, go through legislative and/or technical documents, and scientific and popular papers and define concepts in a specific meaning. An example question from the first tutorial – in which areas it is possible to legally sleep overnight in nature – is modeled in the following way:
Look into the legislation (national, European), if it handles the problem somehow. Find definitions of related terms.
The outcome model shows the relations between the inputs and outputs and shows the way to answer the question. Feel free to use various colours and frame types to express abstract classes, different sources, etc. Use any conceptual language you know to represent the model, e.g. UML or E-R model.
Tutorial models were created in yED.
Based on the model, look for the available data covering the problem. Sources of available data sets are listed in the Semestral Work page. Then create a model of datasets – with objects, their attributes, and relations between objects. Try to think about possible interconnections of concepts of datasets to the concepts in the conceptual model. It may happen that some of the datasets contain crucial information that does not correspond to the conceptual model. Feel free to update the model, but keep in mind, that the conceptual model and model of datasets are at two different levels of modeling (as seen in the picture, where thick lines represent the mapping between dataset models objects to the concept of conceptual model).
Describe datasets in the output document and include the standalone dataset schema diagrams. Describe in the text, how it corresponds to the classes in the conceptual model. Focus on the information needed to answer your question, i.e. interconnecting the data to get the specific knowledge. Superrich data are not useful for you without that one piece of information you need.
Some data are published only regionally. Try to look for other data providing the same or similar knowledge. It may be needed to combine more datasets to complete the knowledge over a larger area.