343 research outputs found
Integrating Historical Person Registers as Linked Open Data in the WarSampo Knowledge Graph
Semantic data integration from heterogeneous, distributed data silos enables Digital Humanities research and application development employing a larger, mutually enriched and interlinked knowledge graph. However, data integration is challenging, involving aligning the data models and reconciling the concepts and named entities, such as persons and places. This paper presents a record linkage process to reconcile person references in different military historical person registers with structured metadata. The information about persons is aggregated into a single knowledge graph. The process was applied to reconcile three person registers of the popular semantic portal "WarSampo -- Finnish World War 2 on the Semantic Web". The registers contain detailed information about some 100,000 people and are individually maintained by domain experts. Thus, the integration process needs to be automatic and adaptable to changes in the registers. An evaluation of the record linkage results is promising and provides some insight into military person register reconciliation in general.Peer reviewe
Using auxiliary data to rationalize smartphone-based pre-harvest forest mensuration
Accurate mensuration of forest stands for pre-harvest planning will pose high costs if carried out by a professional forester as an on-site evaluation. The costs could be reduced if a person with limited mensuration expertise could collect the required data using a smartphone-based system such as TRESTIMA (R) Forest Inventory System. Without prior information, the field sample with sufficient number of measurement points over the whole stand should be selected, so that the entire variation will be covered. We present and test a rational framework based on selecting the sampling locations according to auxiliary data. As auxiliary variables, we use various spatial data sources indicating forests' structural or spectral variation, as well as previously predicted inventory variables. We construct two variants of sampling schemes based on the local pivotal method, weighted by the auxiliary data, and compare the results to simple random sampling (SRS) with corresponding sample sizes. According to our findings, the benefits of auxiliary data depend on the considered stand, species and timber assortment. The use of auxiliary data leads generally to improved results and up to three times higher efficiency (i.e. lower variance) as compared with SRS. We conclude that the framework of applying auxiliary data has high capabilities in rationalizing the sampling efforts with little drawbacks, consequently providing potential to improve the results with similar sample size and possibility to use of non-specialists for the pre-harvest inventory.Peer reviewe
ArCo: the Italian Cultural Heritage Knowledge Graph
ArCo is the Italian Cultural Heritage knowledge graph, consisting of a
network of seven vocabularies and 169 million triples about 820 thousand
cultural entities. It is distributed jointly with a SPARQL endpoint, a software
for converting catalogue records to RDF, and a rich suite of documentation
material (testing, evaluation, how-to, examples, etc.). ArCo is based on the
official General Catalogue of the Italian Ministry of Cultural Heritage and
Activities (MiBAC) - and its associated encoding regulations - which collects
and validates the catalogue records of (ideally) all Italian Cultural Heritage
properties (excluding libraries and archives), contributed by CH administrators
from all over Italy. We present its structure, design methods and tools, its
growing community, and delineate its importance, quality, and impact
New approaches to model and study social networks
We describe and develop three recent novelties in network research which are
particularly useful for studying social systems. The first one concerns the
discovery of some basic dynamical laws that enable the emergence of the
fundamental features observed in social networks, namely the nontrivial
clustering properties, the existence of positive degree correlations and the
subdivision into communities. To reproduce all these features we describe a
simple model of mobile colliding agents, whose collisions define the
connections between the agents which are the nodes in the underlying network,
and develop some analytical considerations. The second point addresses the
particular feature of clustering and its relationship with global network
measures, namely with the distribution of the size of cycles in the network.
Since in social bipartite networks it is not possible to measure the clustering
from standard procedures, we propose an alternative clustering coefficient that
can be used to extract an improved normalized cycle distribution in any
network. Finally, the third point addresses dynamical processes occurring on
networks, namely when studying the propagation of information in them. In
particular, we focus on the particular features of gossip propagation which
impose some restrictions in the propagation rules. To this end we introduce a
quantity, the spread factor, which measures the average maximal fraction of
nearest neighbors which get in contact with the gossip, and find the striking
result that there is an optimal non-trivial number of friends for which the
spread factor is minimized, decreasing the danger of being gossiped.Comment: 16 Pages, 9 figure
The Impact of Intensive Grass Cultivation on Biodiversity - Review
Luken kirjat, raportit, oppaat ja esitteet201
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