Section 3: Going further – using MiMoTextBase for research

Here we would like to exhibit the value and potential of the knowledge graph for different research interests. We intend to address researchers who would like to get an impression of the kind of questions that could be answered with MiMoTextBase. In a first version of the tutorial, we have focused on what we consider to be two very interesting dimensions, namely developments and change over time (i.e. between 1751 and 1800) and comparing different types of sources. The comparison of our different data sources is also interesting as they are based on very different methods. For example, the manually (and humanly) annotated topic concepts of bibliographers from the 1970s can be compared with algorithm-based results from our current topic modeling. By linking different source types in our graph and making them comparable, new amounts of data for a data-based literary history can be obtained. However, the quantitative difference of course also has qualitative dimensions, which we would like to illustrate with the queries in this subsection.

We believe the tutorial is useful for Digital Humanists with an interest in linked open data (especially from Computational Literary Studies, but also all other fields, such as Digital History or Cultural Studies), but also for literary scholars or scholars interested in Book Studies, especially those interested in the Enlightenment as a period and/or the French novel or fictional prose as a genre.

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Where to find…
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… MiMoTextBase: data.mimotext.uni-trier.de
… SPARQL-Endpoint: query.mimotext.uni-trier.de
… MiMoText project site: https://mimotext.uni-trier.de

Am I right here or Where do I start?
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If you are new to SPARQL, you can go through the (short)Tutorial,which will give you an overview of how to write basic queries based on examples inMiMoTextBase. It’s supposed to give newbies an introduction to SPARQL, but it cannot give you a deep knowledge of SPARQL – maybe theseresourcescan help you with that.

If you are interested in MiMoTextBase and its content onauthors,novels,spacesorthemesof the French novel in 1751-1800 with already some SPARQL knowledge, you can have a look at the links.

WithinGOING FURTHER there are some queries on the data containing overviews of items like dates of publication or themes changing over time and comparing the different sources of the data inMiMoTextBase together with some interpretation on the outcome which could show the potential of initial questions on further research.

If you want more detailed information about the structure and the aims of our tutorial, you can find it in theintroduction of the tutorial.Information on the infrastructure and the models behind MiMoTextBase you can findhere.

I have no results. What can I do?
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Having no results in the result table can have different reasons. A simple solution is to check whether the variables are spelled the same in the SELECT and the WHERE part of the query.

Another reason could be being too specific in the query. Not all items in MiMoTextBase contain all information on all properties due to its sources. So it can be helpful to add the OPTIONAL function on some of the properties in your query, seehere.

Error message: Bad aggregate
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If you run into this error message, you probably have to group items. In the example below, we use the count function, but forgot to add GROUP BY.

Query to retrieve count of published works per author:

The solution is easy: We have to aggregate ?authorName by grouping. We can now get the results in descending order via order by desc(?count) and set a limit of 20 to get the top 20.

Query to retrieve authors with most novels published (top 20):

I have too many results. What can I do?
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Sometimes you can get many results on a query which can slow down the result generation or impair the readability of some visualizations. In those cases you could add the LIMIT-operation (seehere)to only get the TOP x items or the HAVING COUNT-operation (seehere)if you want only results that lie above a certain threshold.

If some of the items appear more often in the results than they should, make sure you filter all labels for one language (FR, EN, DE) separately as the graph is multilingual and the output will represent all languages within the graph, seehere.

How to find the right item / right property?
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If you're looking for the right identifier for properties, novels, authors, themes or locations, the simplest way is to visitdata.mimotext.uni-trier.deand type in the label (for example “London” or “about” or “philosophy”) in the search bar. The numerical identifier of the property or the item is visible in the URL or behind the name of the item or the property.

You can also consult our lists of themes, locations and properties and their numerical identifier in the knowledge graph below.

List of properties

Query:Retrieve a list of all the properties used in this graph

List of themes

For a list of all thematic concepts in the graph, see thisquerywhich lists all thematic concepts and their Q-identifier, ordered by occurrence:

List of locations

For a list of all narrative places in the graph, see thisquerywhich lists all narrative places and their Q-Identifier, ordered by occurrence:

These queries list themes or locations ordered by occurrence. We recommend using items or properties which have a certain number of connections in the graph, in order to get good results (with enough data points).

The query is very slow or there is a time out. What can I do?
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There are several possible reasons for a slowdown or a timeout of your query. It could be that the quantity of results is very high, so you might limit the results to check if the syntax of the query is OK. This is done by using theLIMITparameter. The LIMIT tells the algorithm where to stop, so if you insert for example LIMIT 100 at the end of your query, it will stop after 100 results. This can be helpful for debugging.

Parameters which potentially slow down the query are DISTINCT or ORDER BY. A strategy might be to comment them out to see if these slow down your query.