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The Ohsome OSM history analytics platform, developed at HeiGIT, will be presented at the following conferences:

  • ISCRAM in Rochester, NY, USA (20th - 23rd of May)
    In the short paper for the International Conference for Information Systems for Crisis Response and Management we illustrate the specific potential of the ohsome platform for disaster activations by means of two relevant case studies, i.e. the Nepal 2015 earthquake and a comparative evaluation of activations by the Humanitarian OpenStreetMap Team (HOT).

    Auer, M.; Eckle, M.; Fendrich, S.; Griesbaum, L.; Kowatsch, F.; Marx, S.; Raifer, M.; Schott, M.; Troilo, R.; Zipf, A. (2018 accepted): Towards Using the Potential of OpenStreetMap History for Disaster Activation Monitoring. ISCRAM 2018. Rochester, NY, USA.

  • AGIT in Salzburg, Austria (4th - 6th of July)
    At the annual German conference on Applied Geoinformatics in Salzburg, we will give an overview over the Ohsome platform, talk in more detail about the Ohsome API and explain its capabilities through examples.

    Auer, M.; Eckle, M.; Fendrich, S.; Loos, L.; Kowatsch, F.; Marx, S.; Raifer, M.; Schott, M.; Troilo, R.; Zipf, A. (2018 accepted): Eine Plattform zur Analyse raumzeitlicher Entwicklungen von OpenStreetMap-Daten für intrinsische Qualitätsbewertungen. AGIT Symposium, Salzburg, Austria.

  • SotM in Milan, Italy (28th - 30th of July)
    • A workshop as well as a presentation in the academic track of the State of the Map Conference, will be all about Ohsome and its applications.
    • Academic talk

      Auer, M.; Eckle, M.; Fendrich, S.; Kowatsch, F.; Marx, S.; Raifer, M.; Schott, M.; Troilo, R.; Zipf, A. (2018 accepted): Comprehensive OpenStreetMap History Data Analyses - for and with the OSM community. State of the Map Academic Track, Milan.

    • Workshop: Exploring OSM’s history using the “ohsome” data analysis platform. HandsOn Practical!

We are looking forward to meeting you there! Contact us at info@heigit.org if you are interested in getting to know more about the ohsome framework.
ohsome.org

We cordially invite everybody interested to our next open GIScience colloquium talk

The speaker is Mathias Gröbe
Technical University of Dresden, Department of Geosciences, Institute of Cartography

When: Monday 23.04.2018, 14:15

Where: INF 348, room 015 (Institute of Geography, Heidelberg University)

Micro Diagrams: A Multi-Scale Approach for Geovisual Analysis of Categorised Point Datasets

Location-based social media from different platforms such as Twitter and Flickr increasingly serve as data source for many diverse research projects with their point-geocoded content. For analyses and visualisation, it is necessary to show distributions of categories in different scales and resolutions. The Micro Diagrams were developed as solution to map such large geospatial point datasets. For example, a pie chart shows the numerical proportion, and the size or transparency of the chart symbolises the number of records. Therefor an aggregation is necessary to create the diagrams and to map the number of values in one cluster to a visual variable like size. Depending on the aggregation type, the resulting patterns differ. It is possible to choose a convenient method that allows to work with multiple scales with a separate content zoom interaction and to carry out scale-dependent pattern analysis of multivariate point datasets. As visualisation constraint, the area that is used for the representation of the values scales with the numbers of aggregated values.

Again and again each spring it is really awesome (not ohsome ;-) to have a look at our GIScience offices at the Institute of Geography, INF 348, Heidelberg University.

We would like to congratulate Dr. Milutin Milenkovic (Vienna Univ. of Technology, AT) and Dr. Xi Zhu (ITC, NL) for achieving their PhD degree in the domain of 3DGeo research utilizing point clouds from LiDAR and photogrammetry. Bernhard Höfle joined the defenses of the two very good PhD studies:

  • Xi Zhu (2018): Forest Leaf Water Content Estimation Using LiDAR and Hyperspectral Data. ITC, University of Twente, Netherlands.
  • Milutin Milenkovic (2018): Description of Natural Surfaces by Laser Scanning. Department of Geodesy and Geoinformation, Vienna University of Technology.

We can fully recommend to read the papers of Xi and Milutin. Enjoy!

Impressions from Milutin’s defense:

Impressions from Xi’s defense:

The OpenStreetMap History Database (OSHDB) is the main data backend developed at HeiGIT for the ohsome OSM history analytics platform, that will make OSM’s history data more accessible for further analysis. OpenStreetMap (OSM) is a rich resource of freely available geographic information. However, the possibilities for analyzing OSM data on a global scale are limited because of the large amount of resources needed and the lack of easy to use analytics software. That is, OSM’s huge information treasure for researchers, journalists, community members and other interested people is kept hidden. The central idea of the OSHDB is to make this treasure available for a larger public and to develop further analysis functionality, e.g. for intrinsic data quality analytics. We achieve this by employing big data technology that we taylored to the specific needs of OSM’s history data.

In this blog post we briefly introduce the OSHDB API that provides an interface to the OSHDB in the Java programming language. The basic principle of the API is to

(a) select the data you are interested in and

(b) define functions that will compute the desired results from the selected data.

In order to speed up your analyses, the computation can be parallelized on a compute cluster based on the MapReduce programming model.

Let’s look at some Java code to see how easy it is to deploy an analysis:

The first step is to establish a connection to an actual OSHDB database. Several database backends are already available, in this example we use the H2 backend.

  OSHDBDatabase oshdb = new OSHDBH2("path/to/osm-history-extract.oshdb");

Next, we declare a MapReduce-job and link it to the OSHDB:

  MapReducer<OSMEntitySnapshot> mapReducer = OSMEntitySnapshotView.on(oshdb);

In this example, we use a snapshot view that enables us to take snapshots of the OSM data history at given points in time.

Now, we can define our computation. Let’s sum up the total length of mapped motorways in the bounding box of the Maldives at monthly snapshots for the year 2014. As explained above in (a), we first select the relevant data.

  OSHDBBoundingBox boundingBox = Country.getBoundingBox("Maldives");
  mapReducer = mapReducer.areaOfInterest(boundingBox)
    .timestamps("2014-01-01", "2015-01-01", OSHDBTimestamps.Interval.MONTHLY)
    .osmTypes(OSMType.WAY)
    .where("highway", "motorway");

We do so by providing the Maldives’ bounding box as area of interest, the time range from 2014-01-01 to 2015-01-01 in monthly intervals as timestamps and by filtering for OSM ways tagged highway=motorway.

Finally, we define the functions mentioned above in (b).

  SortedMap<OSHDBTimestamp,Number> result = mapReducer.aggregateByTimestamp()
    .map((OSMEntitySnapshot t) -> Geo.lengthOf(t.getGeometry())
    .sum();

The map-step is provided as a lambda expression that takes a snapshot of an OSM entity and returns the length of its geometry. The reduce-step computes the sum of these lengths. Because we told the MapReduce-job to aggregate by timestamp, this reduction is performed for each of our monthly snapshots separately. Therefore, the result is a sorted map that holds the total length of highways as a number for each timestamp.

Stay tuned for further updates of OSHDB and the ohsome OSM-history-analytics platform, such as the forthcoming ohsome API, implemented as REST interfaces, to interactively answer and visualize common predefined research and analyses questions.

ohsome.org

First results of applying OSHDB and ohsome can be found in:

Auer, M.;M. Eckle; S. Fendrich; F. Kowatsch; S. Marx; M. Raifer; M. Schott; R. Troilo; A. Zipf (2018 accepted): Comprehensive OpenStreetMap History Data Analyses - for and with the OSM community. State of the Map Academic Track. Milan.

Points of Interest in Berlin!

Points of Interest in Berlin!

Once again we are extremely excited to announce a new open source project we have been working on over the past few months. To honor the name, we have coined it openpoiservice and it has the simple task of finding points of interest for a given geometry!

To this end, it is able to return poi’s within polygons which can be generated by buffering linestrings, points or simply by providing your own polygon / bounding box.

As with any other project we work on, it extracts information from OpenStreetMap nodes, relations and ways and is able to return GeoJSON features or simple statistics of categories.

You can find the service on GitHub (feel free to contribute, it needs supporters!) and test it within our maps or directly via the openrouteservice API with your own api key.

The service is written in good ol’ Python and it’s terribly easy to set up on your own machine or instance. Please make sure that - depending on the size of the OpenStreetMap file to import - that the specific machine meets the requirements.

The Deadline for submitting short papers to the VGI-ALIVE Workshop at AGILE 2018 has been extended to
23 April 2018!
This is your chance to submit another contribution to this exiting workshop in Lund, Sweden.
Submission format is a workshop short paper (2000 to 3000-word manuscript).

Authors of accepted workshop papers will be invited to submit full papers (maximum 20 pages) to a special issue of the ISPRS International Journal of Geo-Information journal.

For Details see here.

VGI-ALIVE - AnaLysis, Integration, Vision, Engagement. Workshop at AGILE 2018, Lund, Sweden
on
Tuesday 12th June 2018,

VGI-ALIVE Workshop Topics include e.g.:

  • Activity patterns and collaboration across multiple VGI and social media platforms
  • (Quasi) real-time analysis of VGI and social media content
  • Technical and legal aspects of crowd-sourced data fusion
  • Opportunities, challenges, and limitations for the future of VGI
  • VGI/social media analysis in geographic areas with sparse data coverage
  • Novel methods of VGI data quality assessment
  • Mobility patterns and VGI/social media
  • User engagement and VGI education
  • Closing the gaps in VGI data coverage

Exactly 10 years ago openrouteservice.org came online for the very first time. Back then it was the very first online routing service consuming data from OpenStreetMap.org covering larger areas. So to say it is ‘the original‘ OSM routing service. It initially started with Germany only and soon we provided routing for Europe and finally the street network covered the whole globe.

Pascal Neis did a magnificent job with developing the first version, which was embedded in a project on disaster management, which still is a major topic for the current openrouteservice team and further contributors at HeiGIT and GIScience Heidelberg. Since the already impressive beginnings a lot of new features have been added over the years, the whole system has been iteratively enhanced and now we are proud to provide a free API for external users with all different kinds of services and options.

It was a long (and sometimes hard) way from a university project with a single server to a professional and mature API infrastructure and we are happy that we managed to keep it alive and kicking over such a long period of time. This puts it among one of the oldest OSM projects, serving thousands of users and for example even the national German Federal Agency of Cartography and Geodesy (BKG).

The latest list of functionalities includes not only routing, geocoding or isochrones (faster and better than ever) on an interactive web map (maps.openrouteservice.org), but APIs for those and further services such as time-distance matrix calculations or a brand new POI API (openpoiservice) - all with professional documentation. ORS supports more specialised routing profiles than ever: from heavy vehicles, wheelchairs, e-bikes to fitness-level biking and others with many options each. Several dedicated ORS instances for disaster response are updated on high frequency. The isochrone service now supports population statistics, there is a QGIS plugin, geoJSON support, a very handy Python library and - spoiler alert - soon we introduce a library for R users. So stay tuned for the future!

As a research institution we obviously host several research prototypes, e.g. for healthy green & quiet routing, Landmark based navigation, routing across open spaces and much more…

Everything is open source on GitHub

As a special birthday present we will offer a series of JUPYTER notebook examples on how to use the ORS API, starting with - of course - a pub-crawl. Enjoy! We started the tour today with a little birthday cake…

Further information on ORS and related activities can be found in the GIScience Blog and of course at Openrouteservice.org.

Prof. Dr. Alexander Zipf is a invited keynote speaker at the 26th annual GIScience Research UK conference (GISRUK) will be held at the University of Leicester on 17-20 April 2018.

On Thursday April 18th he will give a talk on “Operationalising Volunteered Geographic Information - From Analytics to Improvement and Application“.

Much research has been conducted to better understand the issues with VGI datasets that have now been available for several years as a relatively new kind of spatial data set.For example topics included quality, fitness for purpose, bias or usability among others. A range of methods has been developed to deal with the special characteristics of data produced by volunteers in a little formalised way when analysing it. Many empirical studies have shed some light on the status and the development of those data sources in specific times and regions. Still many questions remain. Because of the high dynamics of the data the half-life of empirical insights is relatively short and because of the heterogeneity very regional studies often are of limited meaningfulness for another context. Influences like culture, language or other geographic aspects need to be examined in more detail and a question that continues to being asked by many practitioners and researchers is: can I use this data for application A or B in region X or Y? We develop an analytics services framework that shall help to answer such kind of questions. In the talk I will present some examples of such analytics of VGI data sets like OSM and social media and some first attempts to develop methods to improve those where possible. This shall finally allow to couple these analytics with real world applications.

Some recent examples of OSM based applications and services developed by GIScience HD /HeiGIT include e.g. Openrouteservice.org (including real-time disaster ORS), the OSM history analytics platform ohsome.org (with a new OSMatrix) , OSMlanduse.org, histOSM.org, MapSwipe Analytics and e.g. the Climate Protection Map (Klimaschutzkarte.de).

Just before the Easter holidays, our GIScience/HeiGIT team hosted Dr. Nama Raj Budhathoki, Executive Director of Kathmandu Living Labs (KLL), to take our existing collaboration to the next level.

KLL and GIScience/HeiGIT have collaborated in various projects in the last few years. GIScience/HeiGIT have contributed to OSM data of Nepal through mapathons in Heidelberg. Relevant contents related to KLL have also been integrated into university courses in Heidelberg. KLL have also shared their experiences regularly with Heidelberg University students through webinars. In addition, KLL has also hosted student interns from Heidelberg University.

Last autumn, this collaboration was strengthened through a Memorandum of Understanding. This reinforced partnership has led to the extension of the OpenRouteService for disaster management and a joint effort on an OSM analytics dashboard to support the use, and understand the progress in OpenStreetMap (OSM) in Nepal and beyond. Both applications advance towards achieving the main objective of this collaboration - to address the existing science-to-society gap by enabling effective use of OSM and other Volunteered Geographic Information (VGI) data.

On the one hand, during Nama’s stay, members of the HeiGIT team had a chance to discuss potential ways to translate cutting-edge scientific work in VGI into implementation in order to better connect data, technology and people. On the other hand, Nama also had the opportunity to meet the HeiGIT team members and to get direct insights into the HeiGIT services and applications. Elaborate exchanges in group meetings and on the Philosophers’ Walk and beyond enabled a broadened understanding of the different approaches of the teams. KLL’s experience on the ground is helpful to design and develop applications and services to increase impacts of their tools and services on the lives of people.

The colloquium presentation furthermore enabled a wider audience to learn about KLL and the team’s background, their current and previous projects related to OSM, disaster management and development, and their future plans.

Follow-up discussions are currently taking place to plan steps ahead for continuing the momentum gained by the partnership and to put ideas into practice towards reducing the science-to-society gap.

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